Title |
|---|
 Understanding and Improving Early Stopping for Learning with Noisy
LabelsNeural Information Processing Systems (NeurIPS), 2021 |
 What Are Bayesian Neural Network Posteriors Really Like?International Conference on Machine Learning (ICML), 2021 |
 On Calibration of Modern Neural NetworksInternational Conference on Machine Learning (ICML), 2017 |
 |
 Stochastic Gradient Hamiltonian Monte CarloInternational Conference on Machine Learning (ICML), 2014 |
 Multi-digit Number Recognition from Street View Imagery using Deep
Convolutional Neural NetworksInternational Conference on Learning Representations (ICLR), 2013 |
 |
 The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian
Monte CarloJournal of machine learning research (JMLR), 2011 Matthew D. Hoffman Andrew Gelman |
