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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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'15
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'25

Papers (including subtopics)

Non-Equilibrium Dynamics of Hybrid Continuous-Discrete Ground-State Sampling ICLR 2025 Nonisotropic Gaussian Diffusion for Realistic 3D Human Motion Prediction CVPR 2025 Nonparametric Bayesian inference of item-level features in classifier combination UAI 2025 Nonparametric Bayesian Multi-Facet Clustering for Longitudinal Data UAI 2025 Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds JMLR 2025 No-Regret Bayesian Optimization with Stochastic Observation Failures AISTATS 2025 NUTMEG: Separating Signal From Noise in Annotator Disagreement EMNLP 2025 Nyström Kernel Stein Discrepancy AISTATS 2025 Offline Changepoint Detection With Gaussian Processes UAI 2025 Offline-to-Online Hyperparameter Transfer for Stochastic Bandits AAAI 2025 Online Student-t Processes with an Overall-local Scale Structure for Modelling Non-stationary Data AISTATS 2025 On the Convergence of Locally Adaptive and Scalable Diffusion-Based Sampling Methods for Deep Bayesian Neural Network Posteriors AISTATS 2025 On the Relationship Between Monotone and Squared Probabilistic Circuits AAAI 2025 On the Trainability and Classical Simulability of Learning Matrix Product States Variationally AAAI 2025 On Tractability of Learning Bayesian Networks with Ancestral Constraints AISTATS 2025 Optimal Submanifold Structure in Log-linear Models UAI 2025 Optimizing Heat Alert Issuance with Reinforcement Learning AAAI 2025 Optimizing Hidden Markov Language Models: An Empirical Study of Reparameterization and Initialization Techniques NAACL 2025 Optimizing Posterior Samples for Bayesian Optimization via Rootfinding ICLR 2025 Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness AISTATS 2025 PABBO: Preferential Amortized Black-Box Optimization ICLR 2025 Parameter estimation in state space models using particle importance sampling AISTATS 2025 pEBR: A Probabilistic Approach to Embedding Based Retrieval EMNLP 2025 pFedGPT: Hierarchically Optimizing LoRA Aggregation Weights for Personalized Federated GPT Models EMNLP 2025 Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time-Series Forecasting Based on Biological ODEs ICLR 2025