conftrace_
← Bayesian & Probabilistic
Artificial Intelligence › Bayesian & Probabilistic ›

Bayesian Learning

1,663 papers

Papers per year

2
48
52
137
36
'05
'10
'15
'20
'25

Papers

Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics AAAI 2020
Fragmentation Coagulation Based Mixed Membership Stochastic Blockmodel AAAI 2020
Generating Well-Formed Answers by Machine Reading with Stochastic Selector Networks AAAI 2020
Few-Shot Bayesian Imitation Learning with Logical Program Policies AAAI 2020
Quantum Probabilistic Models Using Feynman Diagram Rules for Better Understanding the Information Diffusion Dynamics in Online Social Networks AAAI 2020
Mitigating Gender Bias Amplification in Distribution by Posterior Regularization ACL 2020
Towards Interpretable Clinical Diagnosis with Bayesian Network Ensembles Stacked on Entity-Aware CNNs ACL 2020
Bayesian Hierarchical Words Representation Learning ACL 2020
Learning Interpretable Relationships between Entities, Relations and Concepts via Bayesian Structure Learning on Open Domain Facts ACL 2020
Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment ACL 2020
Asynchronous Gibbs Sampling AISTATS 2020
Uncertainty in Neural Networks: Approximately Bayesian Ensembling AISTATS 2020
Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models AISTATS 2020
A Locally Adaptive Bayesian Cubature Method AISTATS 2020
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning AISTATS 2020
Bayesian Image Classification with Deep Convolutional Gaussian Processes AISTATS 2020
Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability AISTATS 2020
Distributionally Robust Bayesian Optimization AISTATS 2020
A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments AISTATS 2020
Bayesian Reinforcement Learning via Deep, Sparse Sampling AISTATS 2020
Monotonic Gaussian Process Flows AISTATS 2020
Learning Ising and Potts Models with Latent Variables AISTATS 2020
Learnable Bernoulli Dropout for Bayesian Deep Learning AISTATS 2020
Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions ALT 2020
Word-Level Uncertainty Estimation for Black-Box Text Classifiers using RNNs COLING 2020