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Bayesian & Probabilistic

4,733 papers (2 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Probabilistic Modeling (2,617) Variational Inference (898) Gaussian Processes (666) Bayesian Learning (483) Markov Chain Monte Carlo (374) Bayesian Optimization (284) Nonparametric Bayesian (174) Bayesian Networks (149) Conditional Random Fields (39)

Papers per year

10
142
164
411
308
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'10
'15
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'25

Papers (including subtopics)

Abductive Reasoning in Logical Credal Networks NeurIPS 2024 A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets NeurIPS 2024 Accelerated Sampling with Stacked Restricted Boltzmann Machines ICLR 2024 Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes NeurIPS 2024 Active Learning Guided by Efficient Surrogate Learners AAAI 2024 Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach AISTATS 2024 Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization AISTATS 2024 Adaptive Latent Feature Sharing for Piecewise Linear Dimensionality Reduction JMLR 2024 Adaptive Meta-Learning Probabilistic Inference Framework for Long Sequence Prediction AAAI 2024 A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators JMLR 2024 Adversarial Causal Bayesian Optimization ICLR 2024 Adversarially-Robust Inference on Trees via Belief Propagation COLT 2024 Adversarial Purification with the Manifold Hypothesis AAAI 2024 A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024 A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024 A General Framework for User-Guided Bayesian Optimization ICLR 2024 A Generalized Bayesian Approach to Distribution-on-Distribution Regression UAI 2024 A General Model for Aggregating Annotations AcrossSimple, Complex, and Multi-object Annotation Tasks (Abstract Reprint) AAAI 2024 A Graph Theoretic Approach for Preference Learning with Feature Information UAI 2024 Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space COLT 2024 Aligning Uncertainty: Leveraging LLMs to Analyze Uncertainty Transfer in Text Summarization EACL 2024 A Metalearned Neural Circuit for Nonparametric Bayesian Inference NeurIPS 2024 Amortized Variational Inference: When and Why? UAI 2024 An Approximate Skolem Function Counter AAAI 2024 A Neural Network Approach for Efficiently Answering Most Probable Explanation Queries in Probabilistic Models NeurIPS 2024