bayesian method

Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization JMLR 2025 Bayesian Low-rank Adaptation for Large Language Models ICLR 2024 Differentially private methods for managing model uncertainty in linear regression JMLR 2024 A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods NeurIPS 2023 GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies NeurIPS 2023 Learning Treatment Effects from Observational and Experimental Data AISTATS 2023 VICE: Variational Interpretable Concept Embeddings NeurIPS 2022 Why the Rich Get Richer? On the Balancedness of Random Partition Models ICML 2022 Hierarchical learning of Hidden Markov Models with clustering regularization UAI 2021 Bayesian Case-Exclusion and Personalized Explanations for Sustainable Dairy Farming (Extended Abstract) IJCAI 2020 DeBayes: a Bayesian Method for Debiasing Network Embeddings ICML 2020 The impact of preprint servers in the formation of novel ideas EMNLP 2020 Bayesian Learning of Neural Network Architectures AISTATS 2019 Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019 From Lab to Internship and Back Again: Learning Autonomous Systems through Creating a Research and Development Ecosystem AAAI 2019 Grounding Referring Expressions in Images by Variational Context CVPR 2018 Post-Inference Prior Swapping ICML 2017 Student-t Process Regression with Student-t Likelihood IJCAI 2017 Demixing odors - fast inference in olfaction NeurIPS 2013 Multiscale Dictionary Learning for Estimating Conditional Distributions NeurIPS 2013 Assessing Blinding in Clinical Trials NeurIPS 2012 Bayesian models for Large-scale Hierarchical Classification NeurIPS 2012 Probabilistic Low-Rank Subspace Clustering NeurIPS 2012 An Empirical Evaluation of Thompson Sampling NeurIPS 2011 Switching state space model for simultaneously estimating state transitions and nonstationary firing rates NeurIPS 2010