{"url":"/task/probabilistic-deep-learning","name":"Probabilistic Deep Learning","slug":"probabilistic-deep-learning","description_markdown":null,"categories":[{"name":"Computer Vision","url":"/area/computer-vision"},{"name":"Knowledge Base","url":"/area/knowledge-base"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":79,"papers_with_code":34,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":6,"subtasks":0,"parent_tasks":0},"benchmarks":[],"datasets":[{"url":"/dataset/dense","name":"DENSE","full_name":"Depth Estimation oN Synthetic Events","num_papers_in_archive":49},{"url":"/dataset/vqa-hat","name":"VQA-HAT","full_name":"VQA Human Attention","num_papers_in_archive":27},{"url":"/dataset/advio","name":"ADVIO","full_name":"","num_papers_in_archive":13},{"url":"/dataset/complete-blood-count-cbc-dataset","name":"CBC","full_name":"Complete Blood Count","num_papers_in_archive":5},{"url":"/dataset/hotel-sales","name":"Hotel","full_name":"Hospitality > Tourism > Hotel Demand/Sales","num_papers_in_archive":2},{"url":"/dataset/data-storage-system-performance","name":"Data Storage System Performance","full_name":"","num_papers_in_archive":1}],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":34,"tagged_in_all":79,"items":[{"url":"/paper/breastscreening-on-the-use-of-multi-modality","title":"BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis","date":"2020-04-07","arxiv_id":"2004.03500","repositories_listed":8,"syntology":null},{"url":"/paper/estimating-and-evaluating-regression","title":"Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors","date":"2021-01-13","arxiv_id":"2101.05036","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":0}},{"url":"/paper/quantum-kernel-mixtures-for-probabilistic","title":"Kernel Density Matrices for Probabilistic Deep Learning","date":"2023-05-26","arxiv_id":"2305.18204","repositories_listed":2,"syntology":null},{"url":"/paper/a-simple-approach-to-improve-single-model","title":"A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness","date":"2022-05-01","arxiv_id":"2205.00403","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/short-term-density-forecasting-of-low-voltage","title":"Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows","date":"2022-04-29","arxiv_id":"2204.13939","repositories_listed":2,"syntology":null},{"url":"/paper/can-you-trust-your-models-uncertainty","title":"Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift","date":"2019-06-06","arxiv_id":"1906.02530","repositories_listed":2,"syntology":null},{"url":"/paper/conditional-deep-surrogate-models-for","title":"Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems","date":"2019-01-15","arxiv_id":"1901.04878","repositories_listed":2,"syntology":null},{"url":"/paper/microcanonical-langevin-ensembles-advancing","title":"Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks","date":"2025-02-10","arxiv_id":"2502.06335","repositories_listed":1,"syntology":null},{"url":"/paper/probabilistic-deep-learning-and-transfer","title":"Probabilistic Deep Learning and Transfer Learning for Robust Cryptocurrency Price Prediction","date":"2024-06-19","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/elastic-full-waveform-inversion-how-the","title":"Integrating Physics of the Problem into Data-Driven Methods to Enhance Elastic Full-Waveform Inversion with Uncertainty Quantification","date":"2024-06-04","arxiv_id":"2406.05153","repositories_listed":1,"syntology":null},{"url":"/paper/stochastic-latent-transformer-efficient","title":"Stochastic Latent Transformer: Efficient Modelling of Stochastically Forced Zonal Jets","date":"2023-10-25","arxiv_id":"2310.16741","repositories_listed":1,"syntology":null},{"url":"/paper/variational-imbalanced-regression","title":"Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing","date":"2023-06-11","arxiv_id":"2306.06599","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_unverified":1,"n_pointer_only":7}},{"url":"/paper/mixture-of-experts-with-uncertainty-voting","title":"Uncertainty Voting Ensemble for Imbalanced Deep Regression","date":"2023-05-24","arxiv_id":"2305.15178","repositories_listed":1,"syntology":{"n":4,"n_ran":0,"n_unverified":4,"n_pointer_only":4}},{"url":"/paper/benchmarking-probabilistic-deep-learning","title":"Benchmarking Probabilistic Deep Learning Methods for License Plate Recognition","date":"2023-02-02","arxiv_id":"2302.01427","repositories_listed":1,"syntology":null},{"url":"/paper/a-self-supervised-approach-to-reconstruction","title":"A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography","date":"2022-10-30","arxiv_id":"2211.00002","repositories_listed":1,"syntology":null},{"url":"/paper/transductive-decoupled-variational-inference","title":"Transductive Decoupled Variational Inference for Few-Shot Classification","date":"2022-08-22","arxiv_id":"2208.10559","repositories_listed":1,"syntology":{"n":8,"n_ran":2,"n_unverified":6,"n_pointer_only":0}},{"url":"/paper/film-ensemble-probabilistic-deep-learning-via","title":"FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation","date":"2022-05-31","arxiv_id":"2206.00050","repositories_listed":1,"syntology":{"n":5,"n_ran":1,"n_unverified":4,"n_pointer_only":0}},{"url":"/paper/a-novel-deep-learning-model-for-hotel-demand","title":"A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19","date":"2022-03-08","arxiv_id":"2203.04383","repositories_listed":1,"syntology":null},{"url":"/paper/bayesflow-can-reliably-detect-model","title":"Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks","date":"2021-12-16","arxiv_id":"2112.08866","repositories_listed":1,"syntology":null},{"url":"/paper/probabilistic-deep-learning-to-quantify","title":"Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting","date":"2021-12-05","arxiv_id":"2112.02622","repositories_listed":1,"syntology":null},{"url":"/paper/probabilistic-metamodels-for-an-efficient","title":"Probabilistic Metamodels for an Efficient Characterization of Complex Driving Scenarios","date":"2021-10-06","arxiv_id":"2110.02892","repositories_listed":1,"syntology":null},{"url":"/paper/probabilistic-deep-learning-for-electric","title":"Probabilistic Deep Learning for Electric-Vehicle Energy-Use Prediction","date":"2021-08-23","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/graph-based-thermal-inertial-slam-with","title":"Graph-based Thermal-Inertial SLAM with Probabilistic Neural Networks","date":"2021-04-15","arxiv_id":"2104.07196","repositories_listed":1,"syntology":null},{"url":"/paper/global-canopy-height-estimation-with-gedi","title":"Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles","date":"2021-03-05","arxiv_id":"2103.03975","repositories_listed":1,"syntology":null},{"url":"/paper/towards-adversarial-robustness-of-bayesian","title":"Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational Inference","date":"2021-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/a-quantum-inspired-probabilistic-model-for","title":"A Quantum-Inspired Probabilistic Model for the Inverse Design of Meta-Structures","date":"2020-11-11","arxiv_id":"2011.05511","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_unverified":1,"n_pointer_only":1}},{"url":"/paper/learning-monocular-dense-depth-from-events","title":"Learning Monocular Dense Depth from Events","date":"2020-10-16","arxiv_id":"2010.08350","repositories_listed":1,"syntology":null},{"url":"/paper/olympus-a-benchmarking-framework-for-noisy","title":"Olympus: a benchmarking framework for noisy optimization and experiment planning","date":"2020-10-08","arxiv_id":"2010.04153","repositories_listed":1,"syntology":null},{"url":"/paper/multi-variate-probabilistic-time-series","title":"Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows","date":"2020-02-14","arxiv_id":"2002.06103","repositories_listed":1,"syntology":null},{"url":"/paper/deepsynth-program-synthesis-for-automatic","title":"DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning","date":"2019-11-22","arxiv_id":"1911.10244","repositories_listed":1,"syntology":null}],"syntology_records":7,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","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)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}