probabilistic programming

Accelerating Metropolis-Hastings with Lightweight Inference Compilation AISTATS 2021 Adapting Coreference Resolution for Processing Violent Death Narratives NAACL 2021 A Language for Counterfactual Generative Models ICML 2021 Automatic structured variational inference AISTATS 2021 Automatic variational inference with cascading flows ICML 2021 Complex Coordinate-Based Meta-Analysis with Probabilistic Programming AAAI 2021 Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model ICML 2021 Efficient Querying for Cooperative Probabilistic Commitments AAAI 2021 Learning proposals for probabilistic programs with inference combinators UAI 2021 Mapping probability word problems to executable representations EMNLP 2021 Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021 Nonparametric Hamiltonian Monte Carlo ICML 2021 PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming AISTATS 2021 Probabilistic Programming Bots in Intuitive Physics Game Play AAAI 2021 Probabilistic Programs with Stochastic Conditioning ICML 2021 The Base Measure Problem and its Solution AISTATS 2021 A Programmatic and Semantic Approach to Explaining and Debugging Neural Network Based Object Detectors CVPR 2020 Automatic Reparameterisation of Probabilistic Programs ICML 2020 Correcting Predictions for Approximate Bayesian Inference AAAI 2020 Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support ICML 2020 Recalibrating classifiers for interpretable abusive content detection EMNLP 2020 Robust, Accurate Stochastic Optimization for Variational Inference NeurIPS 2020 Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models AISTATS 2020 Bayesian Layers: A Module for Neural Network Uncertainty NeurIPS 2019 Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model NeurIPS 2019