bayesian posterior

Can a Bayesian Oracle Prevent Harm from an Agent? UAI 2025 Few-Shot Open-Set Classification via Reasoning-Aware Decomposition EMNLP 2025 How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences JMLR 2025 Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds JMLR 2025 Bias Detection via Signaling NeurIPS 2024 Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective ICLR 2024 On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling JMLR 2024 Posterior Uncertainty Quantification in Neural Networks using Data Augmentation AISTATS 2024 Bayesian Design Principles for Frequentist Sequential Learning ICML 2023 Bayesian Posterior Approximation With Stochastic Ensembles CVPR 2023 Forward-Backward Latent State Inference for Hidden Continuous-Time semi-Markov Chains NeurIPS 2022 PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime AISTATS 2022 BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery NeurIPS 2021 Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification NeurIPS 2021 Is SGD a Bayesian sampler? Well, almost JMLR 2021 Aggregated Gradient Langevin Dynamics AAAI 2020 Asymptotic Consistency of α-Rényi-Approximate Posteriors JMLR 2020 Neural Clustering Processes ICML 2020 A Flexible Generative Framework for Graph-based Semi-supervised Learning NeurIPS 2019 Old Techniques in Differentially Private Linear Regression ALT 2019 On Connecting Stochastic Gradient MCMC and Differential Privacy AISTATS 2019 Kernel Bayesian Inference with Posterior Regularization NeurIPS 2016 Stochastic Gradient Geodesic MCMC Methods NeurIPS 2016 Streaming Variational Bayes NeurIPS 2013