Probabilistic Modeling

Automatic variational inference with cascading flows ICML 2021 A variational approximation for analyzing the dynamics of panel data UAI 2021 Backward-Compatible Prediction Updates: A Probabilistic Approach NeurIPS 2021 Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization AAAI 2021 Bayesian Inference for Optimal Transport with Stochastic Cost ACML 2021 Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions AISTATS 2021 Bayesian Optimization of Function Networks NeurIPS 2021 Bayesian time-aligned factor analysis of paired multivariate time series JMLR 2021 Bayesian Topic Regression for Causal Inference EMNLP 2021 Benchmarking Simulation-Based Inference AISTATS 2021 BERT-Beta: A Proactive Probabilistic Approach to Text Moderation EMNLP 2021 Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation EMNLP 2021 Black Box Probabilistic Numerics NeurIPS 2021 Causal Hidden Markov Model for Time Series Disease Forecasting CVPR 2021 Complex Coordinate-Based Meta-Analysis with Probabilistic Programming AAAI 2021 Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features NeurIPS 2021 Concentric mixtures of Mallows models for top-k rankings: sampling and identifiability ICML 2021 Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression ICML 2021 Conditional Temporal Neural Processes with Covariance Loss ICML 2021 Conditional Variational Capsule Network for Open Set Recognition ICCV 2021 Conformal Bayesian Computation NeurIPS 2021 Context-Aware Online Collective Inference for Templated Graphical Models ICML 2021 Context-dependent Networks in Multivariate Time Series: Models, Methods, and Risk Bounds in High Dimensions JMLR 2021 Context-Specific Likelihood Weighting AISTATS 2021 Contextual Dropout: An Efficient Sample-Dependent Dropout Module ICLR 2021