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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)

Differentially Private Community Detection in Attributed Social Networks ACML 2019
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019
Efficient Inference in Multi-task Cox Process Models AISTATS 2019
Multilingual Factor Analysis ACL 2019
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes NIPS 2019
Efficient Neutrino Oscillation Parameter Inference with Gaussian Process AAAI 2019
Unsupervised Primitive Discovery for Improved 3D Generative Modeling CVPR 2019
Generic Inference in Latent Gaussian Process Models JMLR 2019
CompareLDA: A Topic Model for Document Comparison AAAI 2019
Trust Region Sequential Variational Inference ACML 2019
uniblock: Scoring and Filtering Corpus with Unicode Block Information EMNLP 2019
Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption UAI 2019
Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields IJCAI 2019
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems NIPS 2019
Real-Time Information-Theoretic Exploration with Gaussian Mixture Model Maps RSS 2019
Convergence Guarantees for Adaptive Bayesian Quadrature Methods NIPS 2019
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks NIPS 2018
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches ICML 2018
Proximal Graphical Event Models NIPS 2018
Hamiltonian Variational Auto-Encoder NIPS 2018
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models NIPS 2018
Variational Learning on Aggregate Outputs with Gaussian Processes NIPS 2018
Provable Gaussian Embedding with One Observation NIPS 2018
Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks NIPS 2018
Learning Non-parametric Markov Networks with Mutual Information PGM 2018