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Bayesian Learning

455 papers

Papers per year

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Papers

Robust and Adaptive Deep Learning via Bayesian Principles AAAI 2023
Bayesian Structure Scores for Probabilistic Circuits AISTATS 2023
Overcoming Prior Misspecification in Online Learning to Rank AISTATS 2023
Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery AISTATS 2023
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach AISTATS 2023
Prediction-Oriented Bayesian Active Learning AISTATS 2023
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning EMNLP 2023
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels ICML 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference ICML 2023
Sequential Monte Carlo Learning for Time Series Structure Discovery ICML 2023
A theory of representation learning gives a deep generalisation of kernel methods ICML 2023
Bayesian Federated Learning: A Survey IJCAI 2023
Bayesian Spiked Laplacian Graphs JMLR 2023
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics JMLR 2023
Infinite-dimensional optimization and Bayesian nonparametric learning of stochastic differential equations JMLR 2023
Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance JMLR 2023
Amortized Mixing Coupling Processes for Clustering NIPS 2022
Knowledge-Aware Bayesian Deep Topic Model NIPS 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification NIPS 2022
Online PAC-Bayes Learning NIPS 2022
Model-based Lifelong Reinforcement Learning with Bayesian Exploration NIPS 2022
Globally Gated Deep Linear Networks NIPS 2022
Joint 3D Object Detection and Tracking Using Spatio-Temporal Representation of Camera Image and LiDAR Point Clouds AAAI 2022
Latent Time Neural Ordinary Differential Equations AAAI 2022
Improving Bayesian Neural Networks by Adversarial Sampling AAAI 2022