Bayesian Learning

Learning Ising and Potts Models with Latent Variables AISTATS 2020 Leveraging Document-Level Label Consistency for Named Entity Recognition IJCAI 2020 Making Sense of Reinforcement Learning and Probabilistic Inference ICLR 2020 MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models UAI 2020 Matrix Inference and Estimation in Multi-Layer Models NeurIPS 2020 Meta-Learning PAC-Bayes Priors in Model Averaging AAAI 2020 Meta-trained agents implement Bayes-optimal agents NeurIPS 2020 Mitigating Gender Bias Amplification in Distribution by Posterior Regularization ACL 2020 Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables NeurIPS 2020 Modulating Surrogates for Bayesian Optimization ICML 2020 Monotonic Gaussian Process Flows AISTATS 2020 Multi-objective Bayesian Optimization using Pareto-frontier Entropy ICML 2020 Neural Belief Reasoner IJCAI 2020 Neural Networks with Recurrent Generative Feedback NeurIPS 2020 Non Parametric Graph Learning for Bayesian Graph Neural Networks UAI 2020 Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment ACL 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems AAAI 2020 Online Bayesian Goal Inference for Boundedly Rational Planning Agents NeurIPS 2020 Online Bayesian Persuasion NeurIPS 2020 Optimizing Dynamic Structures with Bayesian Generative Search ICML 2020 Pitfalls of Learning a Reward Function Online IJCAI 2020 PoRB-Nets: Poisson Process Radial Basis Function Networks UAI 2020 Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts NeurIPS 2020 Posterior sampling strategies based on discretized stochastic differential equations for machine learning applications JMLR 2020 Private Bayesian Persuasion with Sequential Games AAAI 2020