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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)

Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
Interpreting Sentiment Composition with Latent Semantic Tree ACL 2023
Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression NIPS 2023
Delayed Feedback in Kernel Bandits ICML 2023
Probabilistic Reasoning and Learning for Trustworthy AI AAAI 2023
MixFlows: principled variational inference via mixed flows ICML 2023
Scale-Invariant Infinite Hierarchical Topic Model ACL 2023
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits NIPS 2023
Multi-Stream Extension of Variational Bayesian HMM Clustering (MS-VBx) for Combined End-to-End and Vector Clustering-based Diarization INTERSPEECH 2023
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification ICML 2023
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels ICML 2023
A Dynamical System View of Langevin-Based Non-Convex Sampling NIPS 2023
Lifted Inference with Linear Order Axiom AAAI 2023
GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks AAAI 2023
Learning-augmented count-min sketches via Bayesian nonparametrics JMLR 2023
Sequential Monte Carlo Learning for Time Series Structure Discovery ICML 2023
Conditional score-based diffusion models for Bayesian inference in infinite dimensions NIPS 2023
VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning NIPS 2023
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model AAAI 2023
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates ICML 2023
A theory of continuous generative flow networks ICML 2023
Inverse-Reference Priors for Fisher Regularization of Bayesian Neural Networks AAAI 2023
Training Energy-Based Normalizing Flow with Score-Matching Objectives NIPS 2023
The Bayesian Learning Rule JMLR 2023
Advancing Bayesian Optimization via Learning Correlated Latent Space NIPS 2023