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Bayesian Learning

455 directly classified papers

Papers per year

Papers

Cautious Bayesian Optimization for Efficient and Scalable Policy Search L4DC 2021
Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning ICCV 2021
Learning local modules in dynamic networks L4DC 2021
Stochastic Transformer Networks With Linear Competing Units: Application To End-to-End SL Translation ICCV 2021
Learning Bayesian Networks from Ordinal Data JMLR 2021
High Dimensional Level Set Estimation with Bayesian Neural Network AAAI 2021
Deep kernel processes ICML 2021
Streaming Bayesian Deep Tensor Factorization ICML 2021
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets NIPS 2021
A General Class of Transfer Learning Regression without Implementation Cost AAAI 2021
Knowledge-Adaptation Priors NIPS 2021
Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning ICML 2021
What Are Bayesian Neural Network Posteriors Really Like? ICML 2021
BORE: Bayesian Optimization by Density-Ratio Estimation ICML 2021
Addressing Catastrophic Forgetting in Few-Shot Problems ICML 2021
Near-Optimal Data Source Selection for Bayesian Learning L4DC 2021
GemBag: Group Estimation of Multiple Bayesian Graphical Models JMLR 2021
Bayesian Nonparametric Space Partitions: A Survey IJCAI 2021
BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks PGM 2020
Theory-Based Causal Transfer:Integrating Instance-Level Induction and Abstract-Level Structure Learning AAAI 2020
GOBNILP: Learning Bayesian network structure with integer programming PGM 2020
Neural Gibbs Sampling for Joint Event Argument Extraction AACL 2020
BCTH: A Novel Text Hashing Approach via Bayesian Clustering AACL 2020
Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions L4DC 2020
L1-GP: L1 Adaptive Control with Bayesian Learning L4DC 2020