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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)

Scalable Approximate MCMC Algorithms for the Horseshoe Prior JMLR 2020
GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020
On Simulation and Trajectory Prediction with Gaussian Process Dynamics L4DC 2020
Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class NIPS 2020
McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020
New Off-Board Solution for Predicting Vehicles' Intentions in the Highway On-Ramp Using Probabilistic Classifiers (Student Abstract) AAAI 2020
Efficient Low Rank Gaussian Variational Inference for Neural Networks NIPS 2020
Hierarchical Dependency Constrained Averaged One-Dependence Estimators Classifiers for Hierarchical Feature Spaces PGM 2020
Bootstrapping neural processes NIPS 2020
A Discrete Variational Recurrent Topic Model without the Reparametrization Trick NIPS 2020
The impact of preprint servers in the formation of novel ideas EMNLP 2020
Kernel-based Approach for Learning Causal Graphs from Mixed Data PGM 2020
Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations AAAI 2020
Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning AAAI 2020
Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020
Sum-Product Network Decompilation PGM 2020
An Expectation Maximisation Algorithm for Automated Cognate Detection EMNLP 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization NIPS 2020
Scaling Up AND/OR Abstraction Sampling IJCAI 2020
Probabilistic Inference for Predicate Constraint Satisfaction AAAI 2020
Training for Gibbs Sampling on Conditional Random Fields with Neural Scoring Factors EMNLP 2020
A Bayesian Approach for Estimating Causal Effects from Observational Data AAAI 2020
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE NIPS 2020
Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions IJCAI 2020
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation ICML 2020