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Bayesian Inference

4,821 papers

Papers per year

Papers

Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components AISTATS 2020
Prior-aware Composition Inference for Spectral Topic Models AISTATS 2020
Scalable Nonparametric Factorization for High-Order Interaction Events AISTATS 2020
Multi-attribute Bayesian optimization with interactive preference learning AISTATS 2020
Stein Variational Inference for Discrete Distributions AISTATS 2020
Nonmyopic Gaussian Process Optimization with Macro-Actions AISTATS 2020
First-Order Bayesian Regret Analysis of Thompson Sampling ALT 2020
Thompson Sampling for Adversarial Bit Prediction ALT 2020
Feedback graph regret bounds for Thompson Sampling and UCB ALT 2020
Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions ALT 2020
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling ALT 2020
Variational Autoencoder with Embedded Student-t Mixture Model for Authorship Attribution COLING 2020
Bayes-enhanced Lifelong Attention Networks for Sentiment Classification COLING 2020
A Deep Generative Distance-Based Classifier for Out-of-Domain Detection with Mahalanobis Space COLING 2020
Bayesian Methods for Semi-supervised Text Annotation COLING 2020
UoB at SemEval-2020 Task 1: Automatic Identification of Novel Word Senses COLING 2020
Sentence Transformers and Bayesian Optimization for Adverse Drug Effect Detection from Twitter COLING 2020
Pessimism About Unknown Unknowns Inspires Conservatism COLT 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo COLT 2020
Wasserstein Control of Mirror Langevin Monte Carlo COLT 2020
An Expectation Maximisation Algorithm for Automated Cognate Detection CONLL 2020
An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference CONLL 2020
Deep Unfolding Network for Image Super-Resolution CVPR 2020
Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring CVPR 2020
Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks CVPR 2020