Bayesian Inference

DiscoBAX: Discovery of optimal intervention sets in genomic experiment design ICML 2023 Discovering Many Diverse Solutions with Bayesian Optimization AISTATS 2023 Discrete Langevin Samplers via Wasserstein Gradient Flow AISTATS 2023 Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation AAAI 2023 Discriminating Known From Unknown Objects via Structure-Enhanced Recurrent Variational AutoEncoder CVPR 2023 Discriminative Calibration: Check Bayesian Computation from Simulations and Flexible Classifier NeurIPS 2023 Disentangled Multi-Fidelity Deep Bayesian Active Learning ICML 2023 Disentangling Learning Representations with Density Estimation ICLR 2023 Distance-to-Set Priors and Constrained Bayesian Inference AISTATS 2023 Distortion and Uncertainty Aware Loss for Panoramic Depth Completion ICML 2023 Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference ICML 2023 Diversity-enhanced probabilistic ensemble for uncertainty estimation UAI 2023 Divide-and-Conquer Fusion JMLR 2023 Do Bayesian Neural Networks Need To Be Fully Stochastic? AISTATS 2023 Does Label Differential Privacy Prevent Label Inference Attacks? AISTATS 2023 Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach ICLR 2023 Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023 DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference ICML 2023 DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization NeurIPS 2023 Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions ICML 2023 Dynamic Belief for Decentralized Multi-Agent Cooperative Learning IJCAI 2023 Effective Bayesian Heteroscedastic Regression with Deep Neural Networks NeurIPS 2023 Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks NeurIPS 2023 Efficient Exploration in Continuous-time Model-based Reinforcement Learning NeurIPS 2023 Efficient Informed Proposals for Discrete Distributions via Newton’s Series Approximation AISTATS 2023