Probabilistic Modeling

QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation NeurIPS 2024 Random measure priors in Bayesian recovery from sketches JMLR 2024 R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning ICLR 2024 Rethinking and Extending the Probabilistic Inference Capacity of GNNs ICLR 2024 Revising Beliefs and Intentions in Stochastic Environments IJCAI 2024 Risk-Calibrated Human-Robot Interaction via Set-Valued Intent Prediction RSS 2024 Risk-sensitive control as inference with Rényi divergence NeurIPS 2024 Robust Approximate Sampling via Stochastic Gradient Barker Dynamics AISTATS 2024 Robust Gaussian Processes via Relevance Pursuit NeurIPS 2024 Robust Uncertainty Quantification Using Conformalised Monte Carlo Prediction AAAI 2024 Sample-Efficient Private Learning of Mixtures of Gaussians NeurIPS 2024 Sampling from the Mean-Field Stationary Distribution COLT 2024 Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits NeurIPS 2024 Scaling Tractable Probabilistic Circuits: A Systems Perspective ICML 2024 ScoreHypo: Probabilistic Human Mesh Estimation with Hypothesis Scoring CVPR 2024 Seeing Unseen: Discover Novel Biomedical Concepts via Geometry-Constrained Probabilistic Modeling CVPR 2024 Sequential Deconfounding for Causal Inference with Unobserved Confounders CLeaR 2024 Serving MPE Queries on Tensor Networks by Computing Derivatives PGM 2024 Simplifying Complex Observation Models in Continuous POMDP Planning with Probabilistic Guarantees and Practice AAAI 2024 SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning ICML 2024 Simulation-Based Stacking AISTATS 2024 Small coresets via negative dependence: DPPs, linear statistics, and concentration NeurIPS 2024 SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents AAAI 2024 Solving High Frequency and Multi-Scale PDEs with Gaussian Processes ICLR 2024 Source-Free Domain-Invariant Performance Prediction ECCV 2024