Massively Scaling Heteroscedastic Classifiers

Massively Scaling Heteroscedastic Classifiers

30 January 2023

Rodolphe Jenatton

Papers citing "Massively Scaling Heteroscedastic Classifiers"

19 / 19 papers shown

Title
Plex: Towards Reliability using Pretrained Large Model Extensions Dustin Tran J. Liu Michael W. Dusenberry Du Phan Mark Collier ... D. Sculley Y. Gal Zoubin Ghahramani Jasper Snoek Balaji Lakshminarayanan VLM 108 126 0 15 Jul 2022
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts Basil Mustafa C. Riquelme J. Puigcerver Rodolphe Jenatton N. Houlsby VLM MoE 156 196 0 06 Jun 2022
LiT: Zero-Shot Transfer with Locked-image text Tuning Xiaohua Zhai Tianlin Li Basil Mustafa Andreas Steiner Daniel Keysers Alexander Kolesnikov Lucas Beyer VLM 95 556 0 15 Nov 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 67 11 0 06 Oct 2021
Scaling Vision with Sparse Mixture of Experts C. Riquelme J. Puigcerver Basil Mustafa Maxim Neumann Rodolphe Jenatton André Susano Pinto Daniel Keysers N. Houlsby MoE 101 600 0 10 Jun 2021
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning Zachary Nado Neil Band Mark Collier Josip Djolonga Michael W. Dusenberry ... D. Sculley Balaji Lakshminarayanan Jasper Snoek Y. Gal Dustin Tran UQCV ELM 74 96 0 07 Jun 2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision Chao Jia Yinfei Yang Ye Xia Yi-Ting Chen Zarana Parekh Hieu H. Pham Quoc V. Le Yun-hsuan Sung Zhen Li Tom Duerig VLM CLIP 443 3,842 0 11 Feb 2021
Are we done with ImageNet? Lucas Beyer Olivier J. Hénaff Alexander Kolesnikov Xiaohua Zhai Aaron van den Oord VLM 119 400 0 12 Jun 2020
Big Transfer (BiT): General Visual Representation Learning Alexander Kolesnikov Lucas Beyer Xiaohua Zhai J. Puigcerver Jessica Yung Sylvain Gelly N. Houlsby MQ 281 1,205 0 24 Dec 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 109 414 0 06 Nov 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 82 808 0 07 Feb 2019
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 176 727 0 13 Jun 2018
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era Chen Sun Abhinav Shrivastava Saurabh Singh Abhinav Gupta VLM 185 2,398 0 10 Jul 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 354 4,705 0 15 Mar 2017
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 1.4K 14,559 0 07 Oct 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy Sergey Ioffe Vincent Vanhoucke Alexander A. Alemi 377 14,247 0 23 Feb 2016
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters Jelena Luketina Mathias Berglund Klaus Greff T. Raiko 55 173 0 20 Nov 2015
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 353 7,936 0 13 Jun 2012
Feature Hashing for Large Scale Multitask Learning Kilian Q. Weinberger A. Dasgupta Josh Attenberg John Langford Alex Smola 116 1,023 0 12 Feb 2009

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