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Bayesian Learning

1,663 papers

Papers per year

2
48
52
137
36
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Papers

Hallucinated adversarial control for conservative offline policy evaluation UAI 2023
A Bayesian approach for bandit online optimization with switching cost UAI 2023
Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement NIPS 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning NIPS 2022
Contrastive Neural Ratio Estimation NIPS 2022
Thompson Sampling Efficiently Learns to Control Diffusion Processes NIPS 2022
Online Neural Sequence Detection with Hierarchical Dirichlet Point Process NIPS 2022
Forward-Backward Latent State Inference for Hidden Continuous-Time semi-Markov Chains NIPS 2022
Posterior and Computational Uncertainty in Gaussian Processes NIPS 2022
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces NIPS 2022
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference NIPS 2022
Learning Optimal Flows for Non-Equilibrium Importance Sampling NIPS 2022
The Neural Testbed: Evaluating Joint Predictions NIPS 2022
Data Augmentation MCMC for Bayesian Inference from Privatized Data NIPS 2022
Byzantine-tolerant federated Gaussian process regression for streaming data NIPS 2022
Independence Testing for Bounded Degree Bayesian Networks NIPS 2022
Active Bayesian Causal Inference NIPS 2022
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination NIPS 2022
Sparse Gaussian Process Hyperparameters: Optimize or Integrate? NIPS 2022
Robust Bayesian Regression via Hard Thresholding NIPS 2022
Adjoint-aided inference of Gaussian process driven differential equations NIPS 2022
Bayesian Risk Markov Decision Processes NIPS 2022
Efficient identification of informative features in simulation-based inference NIPS 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation NIPS 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies NIPS 2022