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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

MOTS: Minimax Optimal Thompson Sampling ICML 2021
Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detection IJCNLP 2021
Bayesian Argumentation-Scheme Networks: A Probabilistic Model of Argument Validity Facilitated by Argumentation Schemes EMNLP 2021
Asymptotics of representation learning in finite Bayesian neural networks NIPS 2021
Asynchronous $ε$-Greedy Bayesian Optimisation UAI 2021
Mixed variable Bayesian optimization with frequency modulated kernels UAI 2021
Exact marginal prior distributions of finite Bayesian neural networks NIPS 2021
Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ACL 2021
Bayesian streaming sparse Tucker decomposition UAI 2021
variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference UAI 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights NIPS 2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing NIPS 2021
Periodic Activation Functions Induce Stationarity NIPS 2021
Dangers of Bayesian Model Averaging under Covariate Shift NIPS 2021
High-dimensional Bayesian optimization with sparse axis-aligned subspaces UAI 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective NIPS 2021
Gone Fishing: Neural Active Learning with Fisher Embeddings NIPS 2021
Learning Bayesian Networks from Ordinal Data JMLR 2021
Near-Optimal Data Source Selection for Bayesian Learning L4DC 2021
Bayesian Topic Regression for Causal Inference EMNLP 2021
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models NIPS 2021
Overcoming Catastrophic Forgetting by Bayesian Generative Regularization ICML 2021
Flexible Signal Denoising via Flexible Empirical Bayes Shrinkage JMLR 2021
Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors JMLR 2021
Tighter Risk Certificates for Neural Networks JMLR 2021