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Bayesian Learning

1663 directly classified papers

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Papers

variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference UAI 2021
GIBBON: General-purpose Information-Based Bayesian Optimisation JMLR 2021
Mixed variable Bayesian optimization with frequency modulated kernels UAI 2021
High-dimensional Bayesian optimization with sparse axis-aligned subspaces UAI 2021
Bayesian streaming sparse Tucker decomposition UAI 2021
AFEC: Active Forgetting of Negative Transfer in Continual Learning NIPS 2021
Asynchronous $ε$-Greedy Bayesian Optimisation UAI 2021
Tighter Risk Certificates for Neural Networks JMLR 2021
Asymptotics of representation learning in finite Bayesian neural networks NIPS 2021
Exact marginal prior distributions of finite Bayesian neural networks NIPS 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights NIPS 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
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors AISTATS 2021
Hyperparameter Transfer Learning with Adaptive Complexity AISTATS 2021
No-Regret Algorithms for Private Gaussian Process Bandit Optimization AISTATS 2021
Predictive Complexity Priors AISTATS 2021
Significance of Gradient Information in Bayesian Optimization AISTATS 2021
Consistency of Gaussian Process Regression in Metric Spaces JMLR 2021
Bayesian Topic Regression for Causal Inference EMNLP 2021
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models NIPS 2021
On Information Gain and Regret Bounds in Gaussian Process Bandits AISTATS 2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing NIPS 2021
Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions AISTATS 2021
Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ACL 2021