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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
'5
'10
'15
'20
'25

Papers (including subtopics)

High Dimensional Bayesian Optimization using Lasso Variable Selection AISTATS 2025 High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching AISTATS 2025 Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation AISTATS 2025 Hypernetwork Approach to Bayesian MAML (Student Abstract) AAAI 2025 Identifiability for Gaussian Processes with Holomorphic Kernels ICLR 2025 Impartial Multi-task Representation Learning via Variance-invariant Probabilistic Decoding ACL 2025 Implicit Diffusion: Efficient optimization through stochastic sampling AISTATS 2025 Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent ICLR 2025 Improving Model Probability Calibration by Integration of Large Data Sources with Biased Labels AAAI 2025 Improving Unsupervised Constituency Parsing via Maximizing Semantic Information ICLR 2025 IRT-Router: Effective and Interpretable Multi-LLM Routing via Item Response Theory ACL 2025 Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs? AISTATS 2025 Kernel-Based Optimal Control: An Infinitesimal Generator Approach L4DC 2025 KernelMatmul: Scaling Gaussian Processes to Large Time Series AAAI 2025 KGE Calibrator: An Efficient Probability Calibration Method of Knowledge Graph Embedding Models for Trustworthy Link Prediction EMNLP 2025 Langevin Monte Carlo Beyond Lipschitz Gradient Continuity AAAI 2025 Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning ICLR 2025 Language Model Probabilities are Not Calibrated in Numeric Contexts ACL 2025 Learnability of Parameter-Bounded Bayes Nets AAAI 2025 Learning Causal Transition Matrix for Instance-dependent Label Noise AAAI 2025 Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood AAAI 2025 Learning Generalized Residual Exchange-Correlation-Uncertain Functional for Density Functional Theory AAAI 2025 Learning High-dimensional Gaussians from Censored Data AISTATS 2025 Learning signals defined on graphs with optimal transport and Gaussian process regression AISTATS 2025 Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators AISTATS 2025