{"about":{"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.","site":"https://codewithpapers.app","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","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/model/papers/42","list_of":"/task/model","task":"model","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":42,"pages_in_order":55,"rows_per_page":100,"rows":[4101,4200],"of":5434,"counts":{"archive_papers_tagged":5434,"with_a_code_link":1733,"where_syntology_ran_a_sample":517,"not_listed_spam_title":0,"listed":5434,"listed_where_code_ran":517,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":424,"every_run_a_failure_of_syntologys_instrument":93,"listed_with_a_run_with_no_instrument_failure":424,"listed_every_run_a_failure_of_syntologys_instrument":93,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/model","prev":"/task/model/papers/41","next":"/task/model/papers/43","papers":[{"url":null,"slug":"visual-semantic-embedding-model-informed-by","title":"Visual-Semantic Embedding Model Informed by Structured Knowledge","date":"2020-09-21","arxiv_id":"2009.10026","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-contraction-approach-to-model-based","title":"A Contraction Approach to Model-based Reinforcement Learning","date":"2020-09-18","arxiv_id":"2009.08586","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-generation-model-a-new-ensemble","title":"Adaptive Generation Model: A New Ensemble Method","date":"2020-09-14","arxiv_id":"2009.06332","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-laundering-for-model-privacy","title":"Information Laundering for Model Privacy","date":"2020-09-13","arxiv_id":"2009.06112","repositories_listed":0,"syntology":null},{"url":null,"slug":"deducing-neighborhoods-of-classes-from-a","title":"Deducing neighborhoods of classes from a fitted model","date":"2020-09-11","arxiv_id":"2009.05516","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-methodological-approach-to-model-cbr-based","title":"A Methodological Approach to Model CBR-based Systems","date":"2020-09-09","arxiv_id":"2009.04346","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-stock-prediction-model-based-on-dcnn","title":"A Stock Prediction Model Based on DCNN","date":"2020-09-07","arxiv_id":"2009.03239","repositories_listed":0,"syntology":null},{"url":null,"slug":"performance-analysis-of-model-free-adaptive","title":"Performance Analysis of Model-Free Adaptive Control","date":"2020-09-07","arxiv_id":"2009.04248","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-parametric-generalized-linear-model","title":"Non-parametric generalized linear model","date":"2020-09-02","arxiv_id":"2009.01362","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-false-alarm-rate-chinese-misspelling","title":"Low False Alarm Rate Chinese Misspelling Detection Model Based on BERT Task Model","date":"2020-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"random-surfing-revisited-generalizing","title":"Random Surfing Revisited: Generalizing PageRank's Teleportation Model","date":"2020-08-29","arxiv_id":"2008.12916","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-spatial-temporal-infection","title":"A comprehensive spatial-temporal infection model","date":"2020-08-28","arxiv_id":"2008.12766","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-model-selection-for-time-series","title":"Automated Model Selection for Time-Series Anomaly Detection","date":"2020-08-25","arxiv_id":"2009.04395","repositories_listed":0,"syntology":null},{"url":"/paper/model-free-episodic-control-with-state","slug":"model-free-episodic-control-with-state","title":"Model-Free Episodic Control with State Aggregation","date":"2020-08-21","arxiv_id":"2008.09685","repositories_listed":0,"syntology":null},{"url":null,"slug":"transforming-probabilistic-programs-for-model","title":"Transforming Probabilistic Programs for Model Checking","date":"2020-08-21","arxiv_id":"2008.09680","repositories_listed":0,"syntology":null},{"url":null,"slug":"analytic-calibration-in-andreasen-huge-sabr","title":"Analytic Calibration in Andreasen-Huge SABR Model","date":"2020-08-20","arxiv_id":"2008.09108","repositories_listed":0,"syntology":null},{"url":"/paper/human-body-model-fitting-by-learned-gradient","slug":"human-body-model-fitting-by-learned-gradient","title":"Human Body Model Fitting by Learned Gradient Descent","date":"2020-08-19","arxiv_id":"2008.08474","repositories_listed":0,"syntology":null},{"url":null,"slug":"transformer-based-multilingual-document","title":"Transformer based Multilingual document Embedding model","date":"2020-08-19","arxiv_id":"2008.08567","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptable-multi-domain-language-model-for","title":"Adaptable Multi-Domain Language Model for Transformer ASR","date":"2020-08-14","arxiv_id":"2008.06208","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dynamic-ordered-logit-model-with-fixed","title":"A dynamic ordered logit model with fixed effects","date":"2020-08-12","arxiv_id":"2008.05517","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-based-offline-planning","title":"Model-Based Offline Planning","date":"2020-08-12","arxiv_id":"2008.05556","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-representation-learning-for-cross","title":"Unified Representation Learning for Cross Model Compatibility","date":"2020-08-11","arxiv_id":"2008.04821","repositories_listed":0,"syntology":null},{"url":null,"slug":"bilevel-learning-model-towards-industrial","title":"Bilevel Learning Model Towards Industrial Scheduling","date":"2020-08-10","arxiv_id":"2008.04130","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatio-temporal-attention-model-for-tactile","title":"Spatio-temporal Attention Model for Tactile Texture Recognition","date":"2020-08-10","arxiv_id":"2008.04442","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-general-solution-to-the-preferential","title":"A general solution to the preferential selection model","date":"2020-08-06","arxiv_id":"2008.02885","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-model-image-annotation-platform-with","title":"Cross-Model Image Annotation Platform with Active Learning","date":"2020-08-06","arxiv_id":"2008.02421","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-dnn-model-with-secret-key-for-model","title":"Training DNN Model with Secret Key for Model Protection","date":"2020-08-06","arxiv_id":"2008.02450","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-learned-performance-model-for-the-tensor","title":"A Learned Performance Model for Tensor Processing Units","date":"2020-08-03","arxiv_id":"2008.01040","repositories_listed":0,"syntology":null},{"url":null,"slug":"anti-bandit-neural-architecture-search-for","title":"Anti-Bandit Neural Architecture Search for Model Defense","date":"2020-08-03","arxiv_id":"2008.00698","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhanced-sparse-model-for-blind-deblurring","title":"Enhanced Sparse Model for Blind Deblurring","date":"2020-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"making-decisions-under-model-misspecification","title":"Making Decisions under Model Misspecification","date":"2020-08-01","arxiv_id":"2008.01071","repositories_listed":0,"syntology":null},{"url":null,"slug":"future-vector-enhanced-lstm-language-model","title":"Future Vector Enhanced LSTM Language Model for LVCSR","date":"2020-07-31","arxiv_id":"2008.01832","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-reduction-of-shallow-cnn-model-for","title":"Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports","date":"2020-07-31","arxiv_id":"2008.01572","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-inference-by-symbolic-model-checking","title":"Bayesian Inference by Symbolic Model Checking","date":"2020-07-29","arxiv_id":"2007.15071","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-simple-and-interpretable-predictive-model","title":"A Simple and Interpretable Predictive Model for Healthcare","date":"2020-07-27","arxiv_id":"2007.13351","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-sound-representation-to-model-robustness","title":"From Sound Representation to Model Robustness","date":"2020-07-27","arxiv_id":"2007.13703","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-bayesian-estimation-in-the","title":"Scalable Bayesian estimation in the multinomial probit model","date":"2020-07-26","arxiv_id":"2007.13247","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-checkers-are-cool-how-to-model-check","title":"Model Checkers Are Cool: How to Model Check Voting Protocols in Uppaal","date":"2020-07-24","arxiv_id":"2007.12412","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-active-learning-by-model","title":"Deep Active Learning by Model Interpretability","date":"2020-07-23","arxiv_id":"2007.12100","repositories_listed":0,"syntology":null},{"url":null,"slug":"initialization-of-a-disease-transmission","title":"Initialization of a Disease Transmission Model","date":"2020-07-17","arxiv_id":"2007.08925","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequential-explanations-with-mental-model","title":"Sequential Explanations with Mental Model-Based Policies","date":"2020-07-17","arxiv_id":"2007.09028","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-world-model-learning-with-progress","title":"Active World Model Learning with Progress Curiosity","date":"2020-07-15","arxiv_id":"2007.07853","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-quantitative-aspects-of-model","title":"On quantitative aspects of model interpretability","date":"2020-07-15","arxiv_id":"2007.07584","repositories_listed":0,"syntology":null},{"url":null,"slug":"vae-lime-deep-generative-model-based-approach","title":"VAE-LIME: Deep Generative Model Based Approach for Local Data-Driven Model Interpretability Applied to the Ironmaking Industry","date":"2020-07-15","arxiv_id":"2007.10256","repositories_listed":0,"syntology":null},{"url":null,"slug":"goal-aware-prediction-learning-to-model-what","title":"Goal-Aware Prediction: Learning to Model What Matters","date":"2020-07-14","arxiv_id":"2007.07170","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-model-for-multi-domain-medical","title":"Universal Model for Multi-Domain Medical Image Retrieval","date":"2020-07-14","arxiv_id":"2007.08628","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-theory-of-interaction-semantics","title":"A model of interaction semantics","date":"2020-07-13","arxiv_id":"2007.06258","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-grained-language-identification-with","title":"Fine-grained Language Identification with Multilingual CapsNet Model","date":"2020-07-12","arxiv_id":"2007.06078","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-value-selection-for-space","title":"Probabilistic Value Selection for Space Efficient Model","date":"2020-07-09","arxiv_id":"2007.04641","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-branching-heuristics-for","title":"Learning Branching Heuristics for Propositional Model Counting","date":"2020-07-07","arxiv_id":"2007.03204","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-model-blind-temporal-denoisers","title":"Learning Model-Blind Temporal Denoisers without Ground Truths","date":"2020-07-07","arxiv_id":"2007.03241","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-nonparametric-latent-class-choice-model","title":"Semi-nonparametric Latent Class Choice Model with a Flexible Class Membership Component: A Mixture Model Approach","date":"2020-07-06","arxiv_id":"2007.02739","repositories_listed":0,"syntology":null},{"url":null,"slug":"space-of-reasons-and-mathematical-model","title":"Space of Reasons and Mathematical Model","date":"2020-07-06","arxiv_id":"2007.02489","repositories_listed":0,"syntology":null},{"url":null,"slug":"selective-dyna-style-planning-under-limited","title":"Selective Dyna-style Planning Under Limited Model Capacity","date":"2020-07-05","arxiv_id":"2007.02418","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-the-covid-19-data-and-the","title":"Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model","date":"2020-07-03","arxiv_id":"2007.02726","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-distillation-beyond-model","title":"Knowledge Distillation Beyond Model Compression","date":"2020-07-03","arxiv_id":"2007.01922","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-distillation-for-revenue-optimization","title":"Model Distillation for Revenue Optimization: Interpretable Personalized Pricing","date":"2020-07-03","arxiv_id":"2007.01903","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-graph-auto-encoder-model-of-derivational","title":"A Graph Auto-encoder Model of Derivational Morphology","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-prioritization-model-for-suicidality-risk","title":"A Prioritization Model for Suicidality Risk Assessment","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchy-aware-global-model-for-hierarchical","title":"Hierarchy-Aware Global Model for Hierarchical Text Classification","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-autoregressive-nmt-with-non","title":"Improving Autoregressive NMT with Non-Autoregressive Model","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-neural-model-for-agglutinative","title":"Multi-Task Neural Model for Agglutinative Language Translation","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tree-structured-neural-topic-model","title":"Tree-Structured Neural Topic Model","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"model-based-reinforcement-learning-a-survey","title":"Model-based Reinforcement Learning: A Survey","date":"2020-06-30","arxiv_id":"2006.16712","repositories_listed":0,"syntology":null},{"url":null,"slug":"hands-off-model-integration-in-spatial-index","title":"Hands-off Model Integration in Spatial Index Structures","date":"2020-06-29","arxiv_id":"2006.16411","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-aware-language-model-pretraining","title":"Knowledge-Aware Language Model Pretraining","date":"2020-06-29","arxiv_id":"2007.00655","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-pure-jump-mean-reverting-short-rate-model","title":"A pure-jump mean-reverting short rate model","date":"2020-06-26","arxiv_id":"2006.14814","repositories_listed":0,"syntology":null},{"url":null,"slug":"control-aware-representations-for-model-based","title":"Control-Aware Representations for Model-based Reinforcement Learning","date":"2020-06-24","arxiv_id":"2006.13408","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-free-voltage-regulation-of-unbalanced","title":"Model-Free Voltage Regulation of Unbalanced Distribution Network Based on Surrogate Model and Deep Reinforcement Learning","date":"2020-06-24","arxiv_id":"2006.13992","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-adversarial-planning-for-indoor","title":"Adversarial Model for Rotated Indoor Scenes Planning","date":"2020-06-24","arxiv_id":"2006.13527","repositories_listed":0,"syntology":null},{"url":null,"slug":"laplacian-mixture-model-point-based","title":"Laplacian Mixture Model Point Based Registration","date":"2020-06-22","arxiv_id":"2006.12582","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-optimism-in-model-based-reinforcement","title":"Towards Tractable Optimism in Model-Based Reinforcement Learning","date":"2020-06-21","arxiv_id":"2006.11911","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-problem-model-selection-for-contextual","title":"Open Problem: Model Selection for Contextual Bandits","date":"2020-06-19","arxiv_id":"2006.10940","repositories_listed":0,"syntology":null},{"url":null,"slug":"federated-learning-with-quantized-global","title":"Federated Learning With Quantized Global Model Updates","date":"2020-06-18","arxiv_id":"2006.10672","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-control-with-learned-dynamics","title":"Data Driven Control with Learned Dynamics: Model-Based versus Model-Free Approach","date":"2020-06-16","arxiv_id":"2006.09543","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-dimensional-model-explanations-an","title":"High Dimensional Model Explanations: an Axiomatic Approach","date":"2020-06-16","arxiv_id":"2006.08969","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-agnostic-combination-for-ensemble","title":"Model Agnostic Combination for Ensemble Learning","date":"2020-06-16","arxiv_id":"2006.09025","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-embedding-model-based-reinforcement","title":"Model Embedding Model-Based Reinforcement Learning","date":"2020-06-16","arxiv_id":"2006.09234","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-explanations-with-differential-privacy","title":"Model Explanations with Differential Privacy","date":"2020-06-16","arxiv_id":"2006.09129","repositories_listed":0,"syntology":null},{"url":null,"slug":"provably-efficient-model-based-policy","title":"Provably Efficient Model-based Policy Adaptation","date":"2020-06-14","arxiv_id":"2006.08051","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-model-based-and-model-free-methods","title":"Combining Model-Based and Model-Free Methods for Nonlinear Control: A Provably Convergent Policy Gradient Approach","date":"2020-06-12","arxiv_id":"2006.07476","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-model-pruning-with-feedback-1","title":"Dynamic Model Pruning with Feedback","date":"2020-06-12","arxiv_id":"2006.07253","repositories_listed":0,"syntology":null},{"url":null,"slug":"complementary-visual-neuronal-systems-model","title":"Complementary Visual Neuronal Systems Model for Collision Sensing","date":"2020-06-11","arxiv_id":"2006.06431","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixup-training-as-the-complexity-reduction","title":"Why Mixup Improves the Model Performance","date":"2020-06-11","arxiv_id":"2006.06231","repositories_listed":0,"syntology":null},{"url":null,"slug":"path-dependent-kyle-equilibrium-model","title":"Path-dependent Kyle equilibrium model","date":"2020-06-11","arxiv_id":"2006.06395","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-limits-to-learning-an-sir-process","title":"The Limits to Learning a Diffusion Model","date":"2020-06-11","arxiv_id":"2006.06373","repositories_listed":0,"syntology":null},{"url":null,"slug":"balancing-fairness-and-efficiency-in-an","title":"Balancing Fairness and Efficiency in an Optimization Model","date":"2020-06-10","arxiv_id":"2006.05963","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-with-multi-layer-embeddings-for","title":"Training with Multi-Layer Embeddings for Model Reduction","date":"2020-06-10","arxiv_id":"2006.05623","repositories_listed":0,"syntology":null},{"url":null,"slug":"regret-balancing-for-bandit-and-rl-model","title":"Regret Balancing for Bandit and RL Model Selection","date":"2020-06-09","arxiv_id":"2006.05491","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-model-based-policy-optimization","title":"Variational Model-based Policy Optimization","date":"2020-06-09","arxiv_id":"2006.05443","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-model-predictive-control-efficient","title":"Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling","date":"2020-06-08","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"edcompress-energy-aware-model-compression","title":"EDCompress: Energy-Aware Model Compression for Dataflows","date":"2020-06-08","arxiv_id":"2006.04588","repositories_listed":0,"syntology":null},{"url":null,"slug":"explicit-option-valuation-in-the-exponential","title":"Explicit option valuation in the exponential NIG model","date":"2020-06-08","arxiv_id":"2006.04659","repositories_listed":0,"syntology":null},{"url":null,"slug":"maximum-entropy-model-rollouts-fast-model","title":"Maximum Entropy Model Rollouts: Fast Model Based Policy Optimization without Compounding Errors","date":"2020-06-08","arxiv_id":"2006.04802","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-model-calibration-with-deep","title":"Real-Time Model Calibration with Deep Reinforcement Learning","date":"2020-06-07","arxiv_id":"2006.04001","repositories_listed":0,"syntology":null},{"url":null,"slug":"handling-missing-data-in-model-based","title":"Handling missing data in model-based clustering","date":"2020-06-04","arxiv_id":"2006.02954","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-model-based-meta-policy-optimization","title":"Meta-Model-Based Meta-Policy Optimization","date":"2020-06-04","arxiv_id":"2006.02608","repositories_listed":0,"syntology":null},{"url":null,"slug":"modified-sir-model-yielding-a-logistic","title":"Modified SIR Model Yielding a Logistic Solution","date":"2020-06-02","arxiv_id":"2006.01550","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-toy-distributional-model-for-fuzzy","title":"A toy distributional model for fuzzy generalised quantifiers","date":"2020-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-generative-model-for-robust-imbalance","title":"Deep Generative Model for Robust Imbalance Classification","date":"2020-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"7daf7df864d8096333e8e3c2b6ce5d2bcbdd44750dca3725e535ea9ce4fa389e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}