Bayesian & Probabilistic

Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021 Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions NeurIPS 2021 Marginalised Gaussian Processes with Nested Sampling NeurIPS 2021 Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021 MARTA: Leveraging Human Rationales for Explainable Text Classification AAAI 2021 Mercer Features for Efficient Combinatorial Bayesian Optimization AAAI 2021 Minimax Estimation of Laplacian Constrained Precision Matrices AISTATS 2021 Modeling Risky Choices in Unknown Environments ACML 2021 Modeling Text using the Continuous Space Topic Model with Pre-Trained Word Embeddings ACL 2021 Modified Frank Wolfe in Probability Space NeurIPS 2021 Modular Self-Supervision for Document-Level Relation Extraction EMNLP 2021 Moment Multicalibration for Uncertainty Estimation COLT 2021 Monte Carlo Variational Auto-Encoders ICML 2021 Moreau-Yosida f-divergences ICML 2021 Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs NeurIPS 2021 Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis JMLR 2021 Near-Optimal Data Source Selection for Bayesian Learning L4DC 2021 Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables NeurIPS 2021 Neural Relation Inference for Multi-dimensional Temporal Point Processes via Message Passing Graph IJCAI 2021 Neural Temporal Point Processes: A Review IJCAI 2021 Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm NeurIPS 2021 Nonparametric Decomposition of Sparse Tensors ICML 2021 Nonparametric Hamiltonian Monte Carlo ICML 2021 Objective Bound Conditional Gaussian Process for Bayesian Optimization ICML 2021 On Empirical Bayes Variational Autoencoder: An Excess Risk Bound COLT 2021