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Bayesian Inference

5,566 papers

Papers per year

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176
522
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Papers

Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks IJCAI 2024
TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction NAACL 2024
Regression Aware Inference with LLMs EMNLP 2024
Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model NIPS 2024
Constrained Sampling with Primal-Dual Langevin Monte Carlo NIPS 2024
PAC-Bayes-Chernoff bounds for unbounded losses NIPS 2024
Coreset Markov chain Monte Carlo AISTATS 2024
Neural Visibility Field for Uncertainty-Driven Active Mapping CVPR 2024
Temperature-scaling surprisal estimates improve fit to human reading times – but does it do so for the “right reasons”? ACL 2024
Provable Posterior Sampling with Denoising Oracles via Tilted Transport NIPS 2024
Probabilistic ODE solvers for integration error-aware numerical optimal control L4DC 2024
Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems JMLR 2024
Scores for Learning Discrete Causal Graphs with Unobserved Confounders AAAI 2024
Full Bayesian Significance Testing for Neural Networks AAAI 2024
More Labels or Cases? Assessing Label Variation in Natural Language Inference EACL 2024
An Analytic Solution to Covariance Propagation in Neural Networks AISTATS 2024
Grey-Box Bayesian Optimization for Sensor Placement in Assisted Living Environments AAAI 2024
Mixed variational flows for discrete variables AISTATS 2024
Globally Convergent Variational Inference NIPS 2024
A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024
Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval NIPS 2024
On Truthing Issues in Supervised Classification JMLR 2024
Physics-constrained learning of PDE systems with uncertainty quantified port-Hamiltonian models L4DC 2024
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization JMLR 2024
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood NIPS 2024