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Bayesian & Probabilistic

4,335 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,599) Bayesian Learning (1,663) Bayesian Inference (523) Variational Inference (107) Gaussian Processes (6) Bayesian Networks (5)

Papers per year

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Papers (including subtopics)

Predictive Uncertainty Estimation for Tractable Deep Probabilistic Models IJCAI 2020
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes NIPS 2020
Causal Inference using Gaussian Processes with Structured Latent Confounders ICML 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks NIPS 2020
Generalized probabilistic principal component analysis of correlated data JMLR 2020
From Support Propagation to Belief Propagation in Constraint Programming (Extended Abstract) IJCAI 2020
Identifying signal and noise structure in neural population activity with Gaussian process factor models NIPS 2020
Sum-Product Network Decompilation PGM 2020
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes JMLR 2020
Generating and Exploiting Probabilistic Monocular Depth Estimates CVPR 2020
Topic Balancing with Additive Regularization of Topic Models ACL 2020
Tuning Causal Discovery Algorithms PGM 2020
What Is It You Really Want of Me? Generalized Reward Learning with Biased Beliefs about Domain Dynamics AAAI 2020
The Unreasonable Effectiveness of Inverse Reinforcement Learning in Advancing Cancer Research AAAI 2020
Private Outsourced Bayesian Optimization ICML 2020
Domain-Liftability of Relational Marginal Polytopes AISTATS 2020
Bayesian Adversarial Human Motion Synthesis CVPR 2020
A Unified Statistically Efficient Estimation Framework for Unnormalized Models AISTATS 2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models ICML 2020
Switching Poisson Gamma Dynamical Systems IJCAI 2020
Streaming Nonlinear Bayesian Tensor Decomposition UAI 2020
Robust, Accurate Stochastic Optimization for Variational Inference NIPS 2020
Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters NIPS 2020
Bootstrapping neural processes NIPS 2020
Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables NIPS 2020