Variational Learning is Effective for Large Deep Networks

27 February 2024

Papers citing "Variational Learning is Effective for Large Deep Networks"

9 / 9 papers shown

Title
Spectral-factorized Positive-definite Curvature Learning for NN Training Wu Lin Felix Dangel Runa Eschenhagen Juhan Bae Richard E. Turner Roger B. Grosse 41 0 0 10 Feb 2025
Streamlining Prediction in Bayesian Deep Learning Rui Li Marcus Klasson Arno Solin Martin Trapp UQCV BDL 91 1 0 27 Nov 2024
A Bayesian Interpretation of Adaptive Low-Rank Adaptation Haolin Chen Philip N. Garner 37 1 0 16 Sep 2024
Wide Mean-Field Bayesian Neural Networks Ignore the Data Beau Coker W. Bruinsma David R. Burt Weiwei Pan Finale Doshi-Velez UQCV BDL 29 21 0 23 Feb 2022
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 264 0 13 Jun 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,927 0 20 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 244 35,884 0 25 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015