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"

10 / 10 papers shown

Title
MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition Nicolas Menet Michael Hersche G. Karunaratne Luca Benini Abu Sebastian Abbas Rahimi 20 13 0 05 Dec 2023
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 53 1 0 02 Nov 2023
DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks Samyak Jain Sravanti Addepalli P. Sahu Priyam Dey R. Venkatesh Babu MoMe OOD 28 20 0 28 Feb 2023
Learn2Weight: Parameter Adaptation against Similar-domain Adversarial Attacks Siddhartha Datta AAML 25 4 0 15 May 2022
Preventing Manifold Intrusion with Locality: Local Mixup Raphael Baena Lucas Drumetz Vincent Gripon AAML 11 15 0 12 Jan 2022
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 85 33 0 03 Jun 2021
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity Jang-Hyun Kim Wonho Choo Hosan Jeong Hyun Oh Song 195 173 0 05 Feb 2021
Knowledge Distillation by On-the-Fly Native Ensemble Xu Lan Xiatian Zhu S. Gong 187 472 0 12 Jun 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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015