{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/vae","entry":"VAE","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":29,"n_papers_ran":18,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":64,"n_samples_ran":37,"n_samples_fingerprinted":7,"n_places":64,"n_places_pointer_only":39,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":37,"unverified":27},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2605.28209","paper":"/paper/arxiv-2605-28209","title":"Robust Contrastive Graph Clustering with Adaptive Local-Global Integration","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"vege12138/w2","path":"model.py","file_url":"https://github.com/vege12138/w2/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"46f1232bb0b2d1b8","mcp_get_code":{"code_sha256":"46f1232bb0b2d1b8"}},{"arxiv_id":"2603.08032","paper":"/paper/arxiv-2603-08032","title":"GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables","date":null,"month_inferred_from_arxiv_id":"2026-03","title_source":"syntology","repo":"decisionintelligence/GCGNet","path":"ts_benchmark/baselines/GCGNet/models/gcgnet_model.py","file_url":"https://github.com/decisionintelligence/GCGNet/blob/HEAD/ts_benchmark/baselines/GCGNet/models/gcgnet_model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bb440cf19c0f42eb","mcp_get_code":{"code_sha256":"bb440cf19c0f42eb"}},{"arxiv_id":"2602.12976","paper":"/paper/arxiv-2602-12976","title":"Drift-Aware Variational Autoencoder-based Anomaly Detection with Two-level Ensembling","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"Jin000001/VAEESDD","path":"class_nn_ae_variational.py","file_url":"https://github.com/Jin000001/VAEESDD/blob/HEAD/class_nn_ae_variational.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e59d60f58d913c0b","mcp_get_code":{"code_sha256":"e59d60f58d913c0b"}},{"arxiv_id":"2509.26074","paper":"/paper/arxiv-2509-26074","title":"Limited Preference Data? Learning Better Reward Model with Latent Space Synthesis","date":null,"month_inferred_from_arxiv_id":"2025-09","title_source":"syntology","repo":"deeplearning-wisc/lens","path":"train_vae_dual.py","file_url":"https://github.com/deeplearning-wisc/lens/blob/HEAD/train_vae_dual.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"5083edb7b2107476","mcp_get_code":{"code_sha256":"5083edb7b2107476"}},{"arxiv_id":"2505.05262","paper":"/paper/enhancing-cooperative-multi-agent","title":"Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration","date":"2025-05-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ddaedalus/smpe","path":"modules/dynamics/variational_inference.py","file_url":"https://github.com/ddaedalus/smpe/blob/HEAD/modules/dynamics/variational_inference.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6899142d57307b36","mcp_get_code":{"code_sha256":"6899142d57307b36"}},{"arxiv_id":"2503.20767","paper":"/paper/reliable-algorithm-selection-for-machine","title":"Reliable algorithm selection for machine learning-guided design","date":"2025-03-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"clarafy/design-algorithm-selection","path":"designers.py","file_url":"https://github.com/clarafy/design-algorithm-selection/blob/HEAD/designers.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"dad11c93ae86fe61","mcp_get_code":{"code_sha256":"dad11c93ae86fe61"}},{"arxiv_id":"2405.19909","paper":"/paper/adaptive-advantage-guided-policy","title":"Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning","date":"2024-05-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ltlhuuu/a2pr","path":"A2PR.py","file_url":"https://github.com/ltlhuuu/a2pr/blob/HEAD/A2PR.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d010e54b60df8f21","mcp_get_code":{"code_sha256":"d010e54b60df8f21"}},{"arxiv_id":"2208.05129","paper":"/paper/robust-reinforcement-learning-using-offline","title":"Robust Reinforcement Learning using Offline Data","date":"2022-08-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zaiyan-x/RFQI","path":"rfqi.py","file_url":"https://github.com/zaiyan-x/RFQI/blob/HEAD/rfqi.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"faab3001b1787a75","mcp_get_code":{"code_sha256":"faab3001b1787a75"}},{"arxiv_id":"2207.08050","paper":"/paper/repairing-systematic-outliers-by-learning-1","title":"Repairing Systematic Outliers by Learning Clean Subspaces in VAEs","date":"2022-07-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sfme/clsvae-error-repair","path":"src/repair_syserr_models/semi_y_CLSVAE.py","file_url":"https://github.com/sfme/clsvae-error-repair/blob/HEAD/src/repair_syserr_models/semi_y_CLSVAE.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"7b62da118d40ebcf","mcp_get_code":{"code_sha256":"7b62da118d40ebcf"}},{"arxiv_id":"2111.08679","paper":"/paper/automatically-detecting-anomalous-exoplanet","title":"Automatically detecting anomalous exoplanet transits","date":"2021-11-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"christophhoenes/anomalousexoplanettransits","path":"architectures.py","file_url":"https://github.com/christophhoenes/anomalousexoplanettransits/blob/HEAD/architectures.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"ae4700404a606f78","mcp_get_code":{"code_sha256":"ae4700404a606f78"}},{"arxiv_id":"2110.12381","paper":"/paper/regularizing-variational-autoencoder-with","title":"Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness","date":"2021-10-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"smilesdzgk/du-vae","path":"modules/vae.py","file_url":"https://github.com/smilesdzgk/du-vae/blob/HEAD/modules/vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"eebe4944ef212d9a","mcp_get_code":{"code_sha256":"eebe4944ef212d9a"}},{"arxiv_id":"2108.13643","paper":"/paper/learning-to-synthesize-programs-as","title":"Learning to Synthesize Programs as Interpretable and Generalizable Policies","date":"2021-08-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"clvrai/leaps","path":"pretrain/models.py","file_url":"https://github.com/clvrai/leaps/blob/HEAD/pretrain/models.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5f52cac9a31533ed","mcp_get_code":{"code_sha256":"5f52cac9a31533ed"}},{"arxiv_id":"2107.11055","paper":"/paper/transporting-causal-mechanisms-for","title":"Transporting Causal Mechanisms for Unsupervised Domain Adaptation","date":"2021-07-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yue-zhongqi/tcm","path":"dda_model/dda_model.py","file_url":"https://github.com/yue-zhongqi/tcm/blob/HEAD/dda_model/dda_model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c365fefa76406516","mcp_get_code":{"code_sha256":"c365fefa76406516"}},{"arxiv_id":"2106.11232","paper":"/paper/multi-vae-learning-disentangled-view-common","title":"Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering","date":"2021-06-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"SubmissionsIn/Multi-VAE","path":"multi_vae/MvModels.py","file_url":"https://github.com/SubmissionsIn/Multi-VAE/blob/HEAD/multi_vae/MvModels.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"b970a3133d958f20","mcp_get_code":{"code_sha256":"b970a3133d958f20"}},{"arxiv_id":"2106.01625","paper":"/paper/generate-prune-select-a-pipeline-for","title":"Generate, Prune, Select: A Pipeline for Counterspeech Generation against Online Hate Speech","date":"2021-06-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"WanzhengZhu/GPS","path":"utility/VAE_Text_Generation/model.py","file_url":"https://github.com/WanzhengZhu/GPS/blob/HEAD/utility/VAE_Text_Generation/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"378aabaa29bf27f8","mcp_get_code":{"code_sha256":"378aabaa29bf27f8"}},{"arxiv_id":"2101.07978","paper":"/paper/semantic-disentangling-generalized-zero","title":"Semantics Disentangling for Generalized Zero-Shot Learning","date":"2021-01-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"uqzhichen/sdgzsl","path":"models.py","file_url":"https://github.com/uqzhichen/sdgzsl/blob/HEAD/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a32115d9a04b5c4b","mcp_get_code":{"code_sha256":"a32115d9a04b5c4b"}},{"arxiv_id":"2101.02477","paper":"/paper/gan-control-explicitly-controllable-gans","title":"GAN-Control: Explicitly Controllable GANs","date":"2021-01-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"amazon-research/gan-control","path":"src/gan_control/models/gan_model.py","file_url":"https://github.com/amazon-research/gan-control/blob/HEAD/src/gan_control/models/gan_model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"93eaf4fe3baa5c5d","mcp_get_code":{"code_sha256":"93eaf4fe3baa5c5d"}},{"arxiv_id":"2010.09164","paper":"/paper/evidential-sparsification-of-multimodal","title":"Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders","date":"2020-10-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sisl/EvidentialSparsification","path":"FashionMNIST/models.py","file_url":"https://github.com/sisl/EvidentialSparsification/blob/HEAD/FashionMNIST/models.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c1882ae03d9d92dc","mcp_get_code":{"code_sha256":"c1882ae03d9d92dc"}},{"arxiv_id":"2007.11301","paper":"/paper/deepsvg-a-hierarchical-generative-network-for","title":"DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation","date":"2020-07-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alexandre01/deepsvg","path":"deepsvg/model/model.py","file_url":"https://github.com/alexandre01/deepsvg/blob/HEAD/deepsvg/model/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"43e61efc110a1a58","mcp_get_code":{"code_sha256":"43e61efc110a1a58"}},{"arxiv_id":"2006.06831","paper":"/paper/algorithmic-recourse-under-imperfect-causal","title":"Algorithmic recourse under imperfect causal knowledge: a probabilistic approach","date":"2020-06-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"amirhk/recourse","path":"_cvae/models.py","file_url":"https://github.com/amirhk/recourse/blob/HEAD/_cvae/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"80322e379aa11111","mcp_get_code":{"code_sha256":"80322e379aa11111"}},{"arxiv_id":"2006.03531","paper":"/paper/a-meta-bayesian-model-of-intentional-visual","title":"A Meta-Bayesian Model of Intentional Visual Search","date":"2020-06-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"v2c08/m-bmvs","path":"mnist_vae.py","file_url":"https://github.com/v2c08/m-bmvs/blob/HEAD/mnist_vae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"GPL-2.0","inline_ok":false,"code_sha256_prefix":"275eddebc797fc46","mcp_get_code":{"code_sha256":"275eddebc797fc46"}},{"arxiv_id":"2006.03531","paper":"/paper/a-meta-bayesian-model-of-intentional-visual","title":"A Meta-Bayesian Model of Intentional Visual Search","date":"2020-06-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"v2c08/M-BMVS","path":"mnist_vae.py","file_url":"https://github.com/v2c08/M-BMVS/blob/HEAD/mnist_vae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"GPL-2.0","inline_ok":false,"code_sha256_prefix":"ba0777a8e08e4344","mcp_get_code":{"code_sha256":"ba0777a8e08e4344"}},{"arxiv_id":"1812.02900","paper":"/paper/off-policy-deep-reinforcement-learning","title":"Off-Policy Deep Reinforcement Learning without Exploration","date":"2018-12-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"maziarg/PrivAttack-BCQ","path":"continuous_BCQ/BCQ.py","file_url":"https://github.com/maziarg/PrivAttack-BCQ/blob/HEAD/continuous_BCQ/BCQ.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a10b65bd9d484e03","mcp_get_code":{"code_sha256":"a10b65bd9d484e03"}},{"arxiv_id":"1812.02900","paper":"/paper/off-policy-deep-reinforcement-learning","title":"Off-Policy Deep Reinforcement Learning without Exploration","date":"2018-12-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thxsxth/POMDP_RLSepsis","path":"RL/other RL attempts/BCQ_models.py","file_url":"https://github.com/thxsxth/POMDP_RLSepsis/blob/HEAD/RL/other%20RL%20attempts/BCQ_models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e3a9f4f45dc4af4e","mcp_get_code":{"code_sha256":"e3a9f4f45dc4af4e"}},{"arxiv_id":"1802.05983","paper":"/paper/disentangling-by-factorising","title":"Disentangling by Factorising","date":"2018-02-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nicolasigor/FactorVAE","path":"factor_vae_mine_v3.py","file_url":"https://github.com/nicolasigor/FactorVAE/blob/HEAD/factor_vae_mine_v3.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b773ab7c4411241a","mcp_get_code":{"code_sha256":"b773ab7c4411241a"}},{"arxiv_id":"1711.00937","paper":"/paper/neural-discrete-representation-learning","title":"Neural Discrete Representation Learning","date":"2017-11-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sisl/MultiAgentVariationalOcclusionInference","path":"src/driver_sensor_model/models_cvae.py","file_url":"https://github.com/sisl/MultiAgentVariationalOcclusionInference/blob/HEAD/src/driver_sensor_model/models_cvae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"1924bf1dbccafe70","mcp_get_code":{"code_sha256":"1924bf1dbccafe70"}},{"arxiv_id":"1611.01144","paper":"/paper/categorical-reparameterization-with-gumbel","title":"Categorical Reparameterization with Gumbel-Softmax","date":"2016-11-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kampta/pytorch-distributions","path":"concrete_vae.py","file_url":"https://github.com/kampta/pytorch-distributions/blob/HEAD/concrete_vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e87691ecef7118db","mcp_get_code":{"code_sha256":"e87691ecef7118db"}},{"arxiv_id":"1611.01144","paper":"/paper/categorical-reparameterization-with-gumbel","title":"Categorical Reparameterization with Gumbel-Softmax","date":"2016-11-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"GuyLor/direct_vae","path":"discrete_vae/GSM.py","file_url":"https://github.com/GuyLor/direct_vae/blob/HEAD/discrete_vae/GSM.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1e08ae9c81b34087","mcp_get_code":{"code_sha256":"1e08ae9c81b34087"}},{"arxiv_id":"1610.02415","paper":"/paper/automatic-chemical-design-using-a-data-driven","title":"Automatic chemical design using a data-driven continuous representation of molecules","date":"2016-10-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Ishan-Kumar2/Molecular_VAE_Pytorch","path":"model.py","file_url":"https://github.com/Ishan-Kumar2/Molecular_VAE_Pytorch/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"9d3e8ba984573f39","mcp_get_code":{"code_sha256":"9d3e8ba984573f39"}},{"arxiv_id":"1511.06349","paper":"/paper/generating-sentences-from-a-continuous-space","title":"Generating Sentences from a Continuous Space","date":"2015-11-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sindhusweety/VAE-Generating-Sentences-From-a-Continuous-Space","path":"model.py","file_url":"https://github.com/sindhusweety/VAE-Generating-Sentences-From-a-Continuous-Space/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7e6ae924c7773d3e","mcp_get_code":{"code_sha256":"7e6ae924c7773d3e"}},{"arxiv_id":"1509.00519","paper":"/paper/importance-weighted-autoencoders","title":"Importance Weighted Autoencoders","date":"2015-09-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"madhubabuv/TightIWAE","path":"model.py","file_url":"https://github.com/madhubabuv/TightIWAE/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"a4a3b579a1c261fb","mcp_get_code":{"code_sha256":"a4a3b579a1c261fb"}},{"arxiv_id":"1509.00519","paper":"/paper/importance-weighted-autoencoders","title":"Importance Weighted Autoencoders","date":"2015-09-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"adrianjav/heterogeneous_vaes","path":"src/models/iwae.py","file_url":"https://github.com/adrianjav/heterogeneous_vaes/blob/HEAD/src/models/iwae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"a4f76a4d4d881d17","mcp_get_code":{"code_sha256":"a4f76a4d4d881d17"}},{"arxiv_id":"1509.00519","paper":"/paper/importance-weighted-autoencoders","title":"Importance Weighted Autoencoders","date":"2015-09-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alexey-pronkin/annealed","path":"avo/models/vae_hvi.py","file_url":"https://github.com/alexey-pronkin/annealed/blob/HEAD/avo/models/vae_hvi.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"f79c21f1eeefc8f3","mcp_get_code":{"code_sha256":"f79c21f1eeefc8f3"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kampta/pytorch-distributions","path":"vae_mnist.py","file_url":"https://github.com/kampta/pytorch-distributions/blob/HEAD/vae_mnist.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8a9443930d373bc6","mcp_get_code":{"code_sha256":"8a9443930d373bc6"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ethanluoyc/pytorch-vae","path":"vae.py","file_url":"https://github.com/ethanluoyc/pytorch-vae/blob/HEAD/vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"9ae83af96c3d86cf","mcp_get_code":{"code_sha256":"9ae83af96c3d86cf"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"adrianjav/heterogeneous_vaes","path":"src/models/vae.py","file_url":"https://github.com/adrianjav/heterogeneous_vaes/blob/HEAD/src/models/vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"4199fb8ac7739853","mcp_get_code":{"code_sha256":"4199fb8ac7739853"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kuc2477/pytorch-vae","path":"model.py","file_url":"https://github.com/kuc2477/pytorch-vae/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ed9f371af886cf81","mcp_get_code":{"code_sha256":"ed9f371af886cf81"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"timbmg/VAE-CVAE-MNIST","path":"models.py","file_url":"https://github.com/timbmg/VAE-CVAE-MNIST/blob/HEAD/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"64b9723a73466fc7","mcp_get_code":{"code_sha256":"64b9723a73466fc7"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"angzhifan/Auto-Encoding_Variational_Bayes","path":"vae_net.py","file_url":"https://github.com/angzhifan/Auto-Encoding_Variational_Bayes/blob/HEAD/vae_net.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8bcd4e1837530f40","mcp_get_code":{"code_sha256":"8bcd4e1837530f40"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sarus-tech/tf2-published-models","path":"vae/model.py","file_url":"https://github.com/sarus-tech/tf2-published-models/blob/HEAD/vae/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"f0219f62556d0e81","mcp_get_code":{"code_sha256":"f0219f62556d0e81"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alexey-pronkin/annealed","path":"avo/models/vae.py","file_url":"https://github.com/alexey-pronkin/annealed/blob/HEAD/avo/models/vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"2f50938796fd893a","mcp_get_code":{"code_sha256":"2f50938796fd893a"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sooooner/MNIST-VAE-with-tensorflow2","path":"utils/model.py","file_url":"https://github.com/sooooner/MNIST-VAE-with-tensorflow2/blob/HEAD/utils/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4dd90798383f2179","mcp_get_code":{"code_sha256":"4dd90798383f2179"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"leokster/CVAE","path":"variational_autoencoder/models.py","file_url":"https://github.com/leokster/CVAE/blob/HEAD/variational_autoencoder/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"f55a416d88ae3f5b","mcp_get_code":{"code_sha256":"f55a416d88ae3f5b"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"KrishnaTarun/Deep-Learning-Lab","path":"assignment_3/code/a3_vae_template.py","file_url":"https://github.com/KrishnaTarun/Deep-Learning-Lab/blob/HEAD/assignment_3/code/a3_vae_template.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0c4e8115a4576c5c","mcp_get_code":{"code_sha256":"0c4e8115a4576c5c"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dungxibo123/vae","path":"VAE/vae.py","file_url":"https://github.com/dungxibo123/vae/blob/HEAD/VAE/vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"afae32e55b46e0c3","mcp_get_code":{"code_sha256":"afae32e55b46e0c3"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"safwankdb/Variational-Auto-Encoder","path":"vae.py","file_url":"https://github.com/safwankdb/Variational-Auto-Encoder/blob/HEAD/vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"94fbbd323c67ac54","mcp_get_code":{"code_sha256":"94fbbd323c67ac54"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"SashaMalysheva/Pytorch-VAE","path":"model.py","file_url":"https://github.com/SashaMalysheva/Pytorch-VAE/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3ffb9653df6d0447","mcp_get_code":{"code_sha256":"3ffb9653df6d0447"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"temirgaliyev/mnist_vae","path":"models.py","file_url":"https://github.com/temirgaliyev/mnist_vae/blob/HEAD/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1bd7bfd13f7b38ba","mcp_get_code":{"code_sha256":"1bd7bfd13f7b38ba"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhengant/vae","path":"model.py","file_url":"https://github.com/zhengant/vae/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"92e95fa0a8df3637","mcp_get_code":{"code_sha256":"92e95fa0a8df3637"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"RoboticsDesignLab/jitterbug","path":"benchmarks/VAE.py","file_url":"https://github.com/RoboticsDesignLab/jitterbug/blob/HEAD/benchmarks/VAE.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a6b5d7a426e105ea","mcp_get_code":{"code_sha256":"a6b5d7a426e105ea"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"seymayucer/VAEs","path":"models/VAE.py","file_url":"https://github.com/seymayucer/VAEs/blob/HEAD/models/VAE.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"80311cacd7cc5b42","mcp_get_code":{"code_sha256":"80311cacd7cc5b42"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dutxiaoli/Vae_for_Photon-counting","path":"vae.py","file_url":"https://github.com/dutxiaoli/Vae_for_Photon-counting/blob/HEAD/vae.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"30c4717f88cc3a7c","mcp_get_code":{"code_sha256":"30c4717f88cc3a7c"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xiangyu-liu/Computer-Network","path":"vae/vae.py","file_url":"https://github.com/xiangyu-liu/Computer-Network/blob/HEAD/vae/vae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7db0725386a21545","mcp_get_code":{"code_sha256":"7db0725386a21545"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"OsvaldN/APS360_Project","path":"VAE/VAE_GAN.py","file_url":"https://github.com/OsvaldN/APS360_Project/blob/HEAD/VAE/VAE_GAN.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"77caa3da6ce1d01a","mcp_get_code":{"code_sha256":"77caa3da6ce1d01a"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"carbonati/variational-zoo","path":"vzoo/models/vae.py","file_url":"https://github.com/carbonati/variational-zoo/blob/HEAD/vzoo/models/vae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0914005903487e9a","mcp_get_code":{"code_sha256":"0914005903487e9a"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"adityabingi/Beta-VAE","path":"model.py","file_url":"https://github.com/adityabingi/Beta-VAE/blob/HEAD/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c1c9d418d2e78caf","mcp_get_code":{"code_sha256":"c1c9d418d2e78caf"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"harish678/PyTorch-Lightning-Examples","path":"vae_lightning.py","file_url":"https://github.com/harish678/PyTorch-Lightning-Examples/blob/HEAD/vae_lightning.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"87a3c3a5c54d6d32","mcp_get_code":{"code_sha256":"87a3c3a5c54d6d32"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wgopar/VariationalAutoencoder","path":"vae.py","file_url":"https://github.com/wgopar/VariationalAutoencoder/blob/HEAD/vae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0cf586eff34a9d1c","mcp_get_code":{"code_sha256":"0cf586eff34a9d1c"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shivakanthsujit/vae-pytorch","path":"VAE.py","file_url":"https://github.com/shivakanthsujit/vae-pytorch/blob/HEAD/VAE.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"d3ad5e47ef3876cb","mcp_get_code":{"code_sha256":"d3ad5e47ef3876cb"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"GuHongyang/VAEs","path":"models/VAE.py","file_url":"https://github.com/GuHongyang/VAEs/blob/HEAD/models/VAE.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"be82b8f3b423d764","mcp_get_code":{"code_sha256":"be82b8f3b423d764"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"davidemartinelli/VAE","path":"model.py","file_url":"https://github.com/davidemartinelli/VAE/blob/HEAD/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"b14d1e688ba813de","mcp_get_code":{"code_sha256":"b14d1e688ba813de"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tegg89/VAE-Tensorflow","path":"model.py","file_url":"https://github.com/tegg89/VAE-Tensorflow/blob/HEAD/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"26fb5b6ee26eee1f","mcp_get_code":{"code_sha256":"26fb5b6ee26eee1f"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shib0li/VAE-PyTorch","path":"models/vae.py","file_url":"https://github.com/shib0li/VAE-PyTorch/blob/HEAD/models/vae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1fef4aa3a0f19616","mcp_get_code":{"code_sha256":"1fef4aa3a0f19616"}},{"arxiv_id":"1312.6114","paper":"/paper/auto-encoding-variational-bayes","title":"Auto-Encoding Variational Bayes","date":"2013-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kpandey008/DiffuseVAE","path":"main/models/vae.py","file_url":"https://github.com/kpandey008/DiffuseVAE/blob/HEAD/main/models/vae.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"349d03ee86dcdb06","mcp_get_code":{"code_sha256":"349d03ee86dcdb06"}}]}