MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks

10 March 2021

Papers citing "MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks"

50 / 99 papers shown

Title
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 85 1 0 02 Nov 2023
Imperceptible Adversarial Examples for Fake Image Detection Quanyu Liao Yuezun Li Xiaoqiang Guo Bin Kong Yingxin Zhu Jianlei Liu Zhuqing Jiang Qi Song Xi Wu AAML 114 33 0 03 Jun 2021
When and How Mixup Improves Calibration Linjun Zhang Zhun Deng Kenji Kawaguchi James Zou UQCV 45 67 0 11 Feb 2021
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity Jang-Hyun Kim Wonho Choo Hosan Jeong Hyun Oh Song 229 180 0 05 Feb 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation Alexandre Ramé Matthieu Cord FedML 64 52 0 14 Jan 2021
ResizeMix: Mixing Data with Preserved Object Information and True Labels Jie Qin Jiemin Fang Qian Zhang Wenyu Liu Xingang Wang Xinggang Wang 53 85 0 21 Dec 2020
Masksembles for Uncertainty Estimation Nikita Durasov Timur M. Bagautdinov Pierre Baqué Pascal Fua OOD UQCV 26 81 0 15 Dec 2020
StackMix: A complementary Mix algorithm John Chen Samarth Sinha Anastasios Kyrillidis 29 3 0 25 Nov 2020
Combining Ensembles and Data Augmentation can Harm your Calibration Yeming Wen Ghassen Jerfel Rafael Muller Michael W. Dusenberry Jasper Snoek Balaji Lakshminarayanan Dustin Tran UQCV 80 63 0 19 Oct 2020
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning Kibok Lee Yian Zhu Kihyuk Sohn Chun-Liang Li Jinwoo Shin Honglak Lee SSL 49 26 0 17 Oct 2020
Training independent subnetworks for robust prediction Marton Havasi Rodolphe Jenatton Stanislav Fort Jeremiah Zhe Liu Jasper Snoek Balaji Lakshminarayanan Andrew M. Dai Dustin Tran UQCV OOD 71 210 0 13 Oct 2020
How Does Mixup Help With Robustness and Generalization? Linjun Zhang Zhun Deng Kenji Kawaguchi Amirata Ghorbani James Zou AAML 64 247 0 09 Oct 2020
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup Jang-Hyun Kim Wonho Choo Hyun Oh Song AAML 55 387 0 15 Sep 2020
On Power Laws in Deep Ensembles E. Lobacheva Nadezhda Chirkova M. Kodryan Dmitry Vetrov UQCV 20 40 0 16 Jul 2020
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning Viktor Olsson Wilhelm Tranheden Juliano Pinto Lennart Svensson 46 336 0 15 Jul 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel Bobby He Balaji Lakshminarayanan Yee Whye Teh BDL UQCV 21 119 0 11 Jul 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 46 207 0 24 Jun 2020
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient Ankit Pensia Shashank Rajput Alliot Nagle Harit Vishwakarma Dimitris Papailiopoulos 43 103 0 14 Jun 2020
GradAug: A New Regularization Method for Deep Neural Networks Taojiannan Yang Sijie Zhu Chong Chen OOD 38 36 0 14 Jun 2020
FenceMask: A Data Augmentation Approach for Pre-extracted Image Features Pu Li Xiangyang Li Xiang Long 21 20 0 14 Jun 2020
SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization A. Uddin Sirazam Monira Wheemyung Shin TaeChoong Chung Sung-Ho Bae 32 228 0 02 Jun 2020
Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? Nadezhda Chirkova E. Lobacheva Dmitry Vetrov OOD MoE 38 9 0 14 May 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 47 209 0 14 May 2020
Milking CowMask for Semi-Supervised Image Classification Geoff French Avital Oliver Tim Salimans 54 52 0 26 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 62 222 0 16 Mar 2020
SuperMix: Supervising the Mixing Data Augmentation Ali Dabouei Sobhan Soleymani Fariborz Taherkhani Nasser M. Nasrabadi 52 99 0 10 Mar 2020
Mixup Regularization for Region Proposal based Object Detectors S. Bouabid V. Delaitre ObjD 43 5 0 04 Mar 2020
A general framework for ensemble distribution distillation Jakob Lindqvist Amanda Olmin Fredrik Lindsten Lennart Svensson FedML UQCV BDL 19 19 0 26 Feb 2020
On Feature Normalization and Data Augmentation Boyi Li Felix Wu Ser-Nam Lim Serge J. Belongie Kilian Q. Weinberger 28 135 0 25 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 46 649 0 20 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 57 315 0 15 Feb 2020
Proving the Lottery Ticket Hypothesis: Pruning is All You Need Eran Malach Gilad Yehudai Shai Shalev-Shwartz Ohad Shamir 93 272 0 03 Feb 2020
The Case for Bayesian Deep Learning A. Wilson UQCV BDL OOD 47 112 0 29 Jan 2020
Hydra: Preserving Ensemble Diversity for Model Distillation Linh-Tam Tran Bastiaan S. Veeling Kevin Roth J. Swiatkowski Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Sebastian Nowozin Rodolphe Jenatton 41 58 0 14 Jan 2020
Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers M. Soflaei Hongyu Guo Ali Al-Bashabsheh Yongyi Mao Richong Zhang MQ 13 8 0 12 Jan 2020
Regularizing Deep Multi-Task Networks using Orthogonal Gradients Mihai Suteu Yike Guo 45 59 0 14 Dec 2019
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty Dan Hendrycks Norman Mu E. D. Cubuk Barret Zoph Justin Gilmer Balaji Lakshminarayanan OOD UQCV 88 1,293 0 05 Dec 2019
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 69 624 0 05 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 256 42,038 0 03 Dec 2019
Online Knowledge Distillation with Diverse Peers Defang Chen Jian-Ping Mei Can Wang Yan Feng Chun-Yen Chen FedML 52 298 0 01 Dec 2019
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring David Berthelot Nicholas Carlini E. D. Cubuk Alexey Kurakin Kihyuk Sohn Han Zhang Colin Raffel 78 676 0 21 Nov 2019
Calibration tests in multi-class classification: A unifying framework David Widmann Fredrik Lindsten Dave Zachariah 46 92 0 24 Oct 2019
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 183 3,458 0 30 Sep 2019
When Does Label Smoothing Help? Rafael Müller Simon Kornblith Geoffrey E. Hinton UQCV 134 1,931 0 06 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 137 1,677 0 06 Jun 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 56 298 0 04 Jun 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 578 4,735 0 13 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 121 3,009 0 06 May 2019
Intra-Ensemble in Neural Networks Yuan Gao Zixiang Cai Chen Sun FedML UQCV 27 5 0 09 Apr 2019
Measuring Calibration in Deep Learning Jeremy Nixon Michael W. Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran UQCV 61 484 0 02 Apr 2019