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Bayesian & Probabilistic

3,963 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,252) Variational Inference (802) Gaussian Processes (570) Bayesian Learning (455) Bayesian Optimization (221) Markov Chain Monte Carlo (143) Nonparametric Bayesian (86) Bayesian Networks (81) Conditional Random Fields (5)

Papers per year

9
118
124
394
151
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Papers (including subtopics)

Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems NIPS 2024
A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets NIPS 2024
A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024
Bayes-optimal learning of an extensive-width neural network from quadratically many samples NIPS 2024
Big Learning Expectation Maximization AAAI 2024
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models AISTATS 2024
A Metalearned Neural Circuit for Nonparametric Bayesian Inference NIPS 2024
Bridge-IF: Learning Inverse Protein Folding with Markov Bridges NIPS 2024
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation NIPS 2024
Spectral Learning of Shared Dynamics Between Generalized-Linear Processes NIPS 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS 2024
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport NIPS 2024
Neural Network Approximators for Marginal MAP in Probabilistic Circuits AAAI 2024
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding NIPS 2024
A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators JMLR 2024
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes NIPS 2024
Symmetric Equilibrium Learning of VAEs AISTATS 2024
Identifiability of Product of Experts Models AISTATS 2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction NIPS 2024
Inversion-based Latent Bayesian Optimization NIPS 2024
Multiple-Source Localization from a Single-Snapshot Observation Using Graph Bayesian Optimization AAAI 2024
Efficiently Acquiring Human Feedback with Bayesian Deep Learning EACL 2024
Classifier Calibration with ROC-Regularized Isotonic Regression AISTATS 2024
Probabilistic Integral Circuits AISTATS 2024
Credal Learning Theory NIPS 2024