Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms

19 September 2023

Papers citing "Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms"

9 / 9 papers shown

Title
Deep Transfer Learning: Model Framework and Error Analysis Yuling Jiao Huazhen Lin Yuchen Luo Jerry Zhijian Yang 41 1 0 12 Oct 2024
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang Victor Veitch OOD 121 32 0 04 Jul 2022
Gradient Matching for Domain Generalization Yuge Shi Jeffrey S. Seely Philip H. S. Torr Siddharth Narayanaswamy Awni Y. Hannun Nicolas Usunier Gabriel Synnaeve OOD 205 246 0 20 Apr 2021
Does Invariant Risk Minimization Capture Invariance? Pritish Kamath Akilesh Tangella Danica J. Sutherland Nathan Srebro OOD 196 125 0 04 Jan 2021
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 900 0 02 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 278 11,677 0 09 Mar 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,356 0 25 Aug 2016
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 156 9,327 0 28 May 2015
Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour M. Mohri Afshin Rostamizadeh 179 788 0 19 Feb 2009