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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)

Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC JMLR 2024 Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo WACV 2024 A probability contrastive learning framework for 3D molecular representation learning NeurIPS 2024 Are You Concerned about Limited Function Evaluations: Data-Augmented Pareto Set Learning for Expensive Multi-Objective Optimization AAAI 2024 A Theory of Non-acyclic Generative Flow Networks AAAI 2024 A Tractable Inference Perspective of Offline RL NeurIPS 2024 Augmented Bayesian Policy Search ICLR 2024 A Unified Framework for Bayesian Optimization under Contextual Uncertainty ICLR 2024 A Unifying Variational Framework for Gaussian Process Motion Planning AISTATS 2024 AutoCD: Automated Machine Learning for Causal Discovery Algorithms PGM 2024 A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs AAAI 2024 A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis NeurIPS 2024 Balancing Computational Cost and Accuracy in Inference of Continuous Bayesian Networks PGM 2024 Batched Energy-Entropy acquisition for Bayesian Optimization NeurIPS 2024 Bayesian Adaptive Calibration and Optimal Design NeurIPS 2024 Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures ICLR 2024 Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NeurIPS 2024 Bayesian Exploration of Pre-trained Models for Low-shot Image Classification CVPR 2024 Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization NeurIPS 2024 Bayesian Online Learning for Consensus Prediction AISTATS 2024 Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal NeurIPS 2024 Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data ICLR 2024 Bayesian Pseudo-Coresets via Contrastive Divergence UAI 2024 Bayes-optimal learning of an extensive-width neural network from quadratically many samples NeurIPS 2024 Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024