Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration

1 October 2021

Papers citing "Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration"

6 / 6 papers shown

Title
Sparse Deep Learning for Time Series Data: Theory and Applications Mingxuan Zhang Y. Sun Faming Liang AI4TS OOD BDL 44 2 0 05 Oct 2023
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks Daiwei Zhang Tianci Liu Jian Kang BDL UQCV 43 2 0 12 Jun 2022
Consistent Sparse Deep Learning: Theory and Computation Y. Sun Qifan Song F. Liang BDL 48 27 0 25 Feb 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,695 0 05 Dec 2016
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 40 159 0 21 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015