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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Ensuring Reliable and Transparent Algorithmic Fairness Through Optimal Transport and Uncertainty Quantification IJCAI 2025
From Your Block to Our Block: How to Find Shared Structure Between Stochastic Block Models over Multiple Graphs AAAI 2025
Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models IJCAI 2025
BUFF: Bayesian Uncertainty Guided Diffusion Probabilistic Model for Single Image Super-Resolution AAAI 2025
Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds JMLR 2025
FlowDPS : Flow-Driven Posterior Sampling for Inverse Problems ICCV 2025
Diffusion Models for Attribution AAAI 2025
EMControl: Adding Conditional Control to Text-to-Image Diffusion Models via Expectation-Maximization AAAI 2025
Bayesian Score Calibration for Approximate Models JMLR 2025
Task Calibration: Calibrating Large Language Models on Inference Tasks ACL 2025
Robust Heterogeneous Graph Classification for Molecular Property Prediction with Information Bottleneck AAAI 2025
Partially Blinded Unlearning: Class Unlearning for Deep Networks from Bayesian Perspective AAAI 2025
Distilling Rule-based Knowledge into Large Language Models COLING 2025
Entire-Space Variational Information Exploitation for Post-Click Conversion Rate Prediction AAAI 2025
Agreement-Constrained Probabilistic Minimum Bayes Risk Decoding IJCNLP 2025
Explicit Bayesian Inference to Uncover the Latent Themes of Large Language Models ACL 2025
Quantized Can Still Be Calibrated: A Unified Framework to Calibration in Quantized Large Language Models ACL 2025
Combining Priors with Experience: Confidence Calibration Based on Binomial Process Modeling AAAI 2025
MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media NAACL 2025
Benchmarking Uncertainty Metrics for LLM Target-Aware Search EMNLP 2025
Density Uncertainty Layers for Reliable Uncertainty Estimation AISTATS 2024
Reparameterized Variational Rejection Sampling AISTATS 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels AISTATS 2024
A Hypothesis-Driven Framework for the Analysis of Self-Rationalising Models EACL 2024
Lower Bounds on the Bayesian Risk via Information Measures JMLR 2024