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Bayesian & Probabilistic

5,407 papers (3 classified directly here)

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

Probabilistic Modeling (3,137) Bayesian Learning (1,734) Bayesian Inference (1,087) Variational Inference (275) Bayesian Networks (103) Gaussian Processes (88)

Papers per year

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2000
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Papers (including subtopics)

Variational Phylogenetic Inference with Products over Bipartitions ICML 2025 Variation Due to Regularization Tractably Recovers Bayesian Deep Learning Uncertainty AISTATS 2025 Walk the Talk? Measuring the Faithfulness of Large Language Model Explanations ICLR 2025 Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context AISTATS 2025 Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference AISTATS 2025 Well-Defined Function-Space Variational Inference in Bayesian Neural Networks via Regularized KL-Divergence UAI 2025 What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization AISTATS 2025 Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices ICML 2025 $ρ$-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows PGM 2024 $Ψ$net: Efficient Causal Modeling at Scale PGM 2024 3D Gaussian Splatting as Markov Chain Monte Carlo NeurIPS 2024 A Bayesian Approach to Data Point Selection NeurIPS 2024 A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution EMNLP 2024 A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent AISTATS 2024 A Bayesian Quantification of Aporophobia and the Aggravating Effect of Low–Wealth Contexts on Stigmatization NAACL 2024 A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing AAAI 2024 Abductive Reasoning in Logical Credal Networks NeurIPS 2024 Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex AISTATS 2024 Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes NeurIPS 2024 Adaptive Meta-Learning Probabilistic Inference Framework for Long Sequence Prediction AAAI 2024 Additive smoothing error in backward variational inference for general state-space models JMLR 2024 A Divide and Conquer Approach for Solving Structural Causal Models PGM 2024 A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetics NeurIPS 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