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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Efficient Out-of-Scope Detection in Dialogue Systems via Uncertainty-Driven LLM Routing ACL 2025
Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes JMLR 2025
Statistical Inference of Random Graphs With a Surrogate Likelihood Function JMLR 2025
Relaxed Gaussian Process Interpolation: a Goal-Oriented Approach to Bayesian Optimization JMLR 2025
Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty Detection JMLR 2025
Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation JMLR 2025
BayesCNS: A Unified Bayesian Approach to Address Cold Start and Non-Stationarity in Search Systems at Scale AAAI 2025
RLKGF: Reinforcement Learning from Knowledge Graph Feedback Without Human Annotations ACL 2025
Inferring Change Points in High-Dimensional Regression via Approximate Message Passing JMLR 2025
A Bayesian Approach to Inferring Prerequisite Structures and Topic Difficulty in Language Learning ACL 2025
Scalable and Adaptive Variational Bayes Methods for Hawkes Processes JMLR 2025
SafeConf: A Confidence-Calibrated Safety Self-Evaluation Method for Large Language Models EMNLP 2025
Beyond the First Error: Process Reward Models for Reflective Mathematical Reasoning EMNLP 2025
Expected Hypervolume Improvement Is a Particular Hypervolume Improvement AAAI 2025
User Preference Meets Pareto-Optimality in Multi-Objective Bayesian Optimization AAAI 2025
Resource-Rational Noisy-Channel Language Processing: Testing the Effect of Algorithmic Constraints on Inferences EMNLP 2025
KGE Calibrator: An Efficient Probability Calibration Method of Knowledge Graph Embedding Models for Trustworthy Link Prediction EMNLP 2025
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples JMLR 2025
Langevin Monte Carlo Beyond Lipschitz Gradient Continuity AAAI 2025
An Asymptotically Optimal Coordinate Descent Algorithm for Learning Bayesian Networks from Gaussian Models JMLR 2025
From Your Block to Our Block: How to Find Shared Structure Between Stochastic Block Models over Multiple Graphs AAAI 2025
Backward Filtering Forward Guiding JMLR 2025
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation CVPR 2025
ProHOC: Probabilistic Hierarchical Out-of-Distribution Classification via Multi-Depth Networks CVPR 2025
Generalization-Preserved Learning: Closing the Backdoor to Catastrophic Forgetting in Continual Deepfake Detection ICCV 2025