Bayesian Inference

Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo ICML 2025 Spike-and-Slab Posterior Sampling in High Dimensions COLT 2025 Statistical field theory for Markov decision processes under uncertainty JMLR 2025 Statistical Inference of Random Graphs With a Surrogate Likelihood Function JMLR 2025 Steering Protein Family Design through Profile Bayesian Flow ICLR 2025 Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design ICML 2025 Stochasticity-aware No-Reference Point Cloud Quality Assessment IJCAI 2025 Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold ICLR 2025 Streamlining Prediction in Bayesian Deep Learning ICLR 2025 Structure-Conditional Minimum Bayes Risk Decoding EMNLP 2025 SUE: Sparsity-based Uncertainty Estimation via Sparse Dictionary Learning EMNLP 2025 Surprise Calibration for Better In-Context Learning EMNLP 2025 syftr: Pareto-Optimal Generative AI AutoML 2025 SyncSDE: A Probabilistic Framework for Diffusion Synchronization CVPR 2025 Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo ICLR 2025 Tamed Langevin sampling under weaker conditions AISTATS 2025 TASAR: Transfer-based Attack on Skeletal Action Recognition ICLR 2025 Task Calibration: Calibrating Large Language Models on Inference Tasks ACL 2025 Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals ACL 2025 Test-time Adaptation for Foundation Medical Segmentation Model Without Parametric Updates ICCV 2025 Test-time Adaptation for Image Compression with Distribution Regularization ICLR 2025 The interventional Bayesian Gaussian equivalent score for Bayesian causal inference with unknown soft interventions CLeaR 2025 The Lessons of Developing Process Reward Models in Mathematical Reasoning ACL 2025 Theoretical Guarantees for Minimum Bayes Risk Decoding ACL 2025 The Polynomial Stein Discrepancy for Assessing Moment Convergence ICML 2025