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Bayesian & Probabilistic

3,963 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,252) Variational Inference (802) Gaussian Processes (570) Bayesian Learning (455) Bayesian Optimization (221) Markov Chain Monte Carlo (143) Nonparametric Bayesian (86) Bayesian Networks (81) Conditional Random Fields (5)

Papers per year

9
118
124
394
151
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Papers (including subtopics)

Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge IJCAI 2020
Learning under Model Misspecification: Applications to Variational and Ensemble methods NIPS 2020
Learning of Sub-optimal Gait Controllers for Magnetic Walking Soft Millirobots RSS 2020
Scaling Up AND/OR Abstraction Sampling IJCAI 2020
Generalised Bayesian Filtering via Sequential Monte Carlo NIPS 2020
ASR-Free Pronunciation Assessment INTERSPEECH 2020
An Efficient Low-Rank Tensors Representation for Algorithms in Complex Probabilistic Graphical Models PGM 2020
On Application of Bayesian Parametric and Non-parametric Methods for User Cohorting in Product Search ACL 2020
Parametric Gaussian Process Regressors ICML 2020
Fast and Flexible Temporal Point Processes with Triangular Maps NIPS 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning NIPS 2020
Robust, Accurate Stochastic Optimization for Variational Inference NIPS 2020
Learning Robot Skills with Temporal Variational Inference ICML 2020
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization NIPS 2020
Switching Poisson Gamma Dynamical Systems IJCAI 2020
From Support Propagation to Belief Propagation in Constraint Programming (Extended Abstract) IJCAI 2020
Diversified Interactive Recommendation with Implicit Feedback AAAI 2020
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond NIPS 2020
Interpretable Deep Gaussian Processes with Moments AISTATS 2020
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking NIPS 2020
Neural Dialogue State Tracking with Temporally Expressive Networks EMNLP 2020
Experimental Design for Optimization of Orthogonal Projection Pursuit Models AAAI 2020
Federated Bayesian Optimization via Thompson Sampling NIPS 2020
Multi-task Causal Learning with Gaussian Processes NIPS 2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models ICML 2020