Bayesian & Probabilistic

On Energy-Based Models with Overparametrized Shallow Neural Networks ICML 2021 On Estimation in Latent Variable Models ICML 2021 Online Learning of a Probabilistic and Adaptive Scene Representation CVPR 2021 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization ICML 2021 On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes ICML 2021 On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness COLT 2021 On the difficulty of unbiased alpha divergence minimization ICML 2021 On the Stochastic Stability of Deep Markov Models NeurIPS 2021 On Variational Inference in Biclustering Models ICML 2021 Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm COLT 2021 Optimal Order Simple Regret for Gaussian Process Bandits NeurIPS 2021 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search ICML 2021 Optimal Underdamped Langevin MCMC Method NeurIPS 2021 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation ICML 2021 Parametric Distributions to Model Numerical Emotion Labels Interspeech 2021 Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions ICML 2021 Partition Function Estimation: A Quantitative Study IJCAI 2021 Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression AAAI 2021 Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning ICCV 2021 Predictive Learning on Hidden Tree-Structured Ising Models JMLR 2021 Probabilistic 3D Human Shape and Pose Estimation From Multiple Unconstrained Images in the Wild CVPR 2021 Probabilistic Embeddings for Cross-Modal Retrieval CVPR 2021 Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs NeurIPS 2021 Probabilistic Generating Circuits ICML 2021 Probabilistic Modeling for Human Mesh Recovery ICCV 2021