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Task Guided Compositional Representation Learning for ZDA

Task Guided Compositional Representation Learning for ZDA

13 September 2021
Shuang Liu
Mete Ozay
    OOD
ArXivPDFHTML

Papers citing "Task Guided Compositional Representation Learning for ZDA"

21 / 21 papers shown
Title
Does Invariant Risk Minimization Capture Invariance?
Does Invariant Risk Minimization Capture Invariance?
Pritish Kamath
Akilesh Tangella
Danica J. Sutherland
Nathan Srebro
OOD
245
128
0
04 Jan 2021
Environment Inference for Invariant Learning
Environment Inference for Invariant Learning
Elliot Creager
J. Jacobsen
R. Zemel
OOD
57
382
0
14 Oct 2020
Understanding the Role of Individual Units in a Deep Neural Network
Understanding the Role of Individual Units in a Deep Neural Network
David Bau
Jun-Yan Zhu
Hendrik Strobelt
Àgata Lapedriza
Bolei Zhou
Antonio Torralba
GAN
65
449
0
10 Sep 2020
In Search of Lost Domain Generalization
In Search of Lost Domain Generalization
Ishaan Gulrajani
David Lopez-Paz
OOD
74
1,137
0
02 Jul 2020
Do We Really Need to Access the Source Data? Source Hypothesis Transfer
  for Unsupervised Domain Adaptation
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Jian Liang
Dapeng Hu
Jiashi Feng
93
1,238
0
20 Feb 2020
The Unreasonable Effectiveness of Deep Learning in Artificial
  Intelligence
The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence
T. Sejnowski
38
298
0
12 Feb 2020
Adversarial Domain Adaptation with Domain Mixup
Adversarial Domain Adaptation with Domain Mixup
Minghao Xu
Jian Zhang
Bingbing Ni
Teng Li
Chengjie Wang
Qi Tian
Wenjun Zhang
52
447
0
04 Dec 2019
Discriminative Adversarial Domain Adaptation
Discriminative Adversarial Domain Adaptation
Hui Tang
Kui Jia
OOD
60
194
0
27 Nov 2019
Theoretical Issues in Deep Networks: Approximation, Optimization and
  Generalization
Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization
T. Poggio
Andrzej Banburski
Q. Liao
ODL
69
164
0
25 Aug 2019
$d$-SNE: Domain Adaptation using Stochastic Neighborhood Embedding
ddd-SNE: Domain Adaptation using Stochastic Neighborhood Embedding
Xiang Xu
Xiong Zhou
Ragav Venkatesan
Gurumurthy Swaminathan
Orchid Majumder
51
120
0
29 May 2019
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
Chen-Yu Lee
Tanmay Batra
M. H. Baig
Daniel Ulbricht
116
541
0
10 Mar 2019
Support and Invertibility in Domain-Invariant Representations
Support and Invertibility in Domain-Invariant Representations
Fredrik D. Johansson
David Sontag
Rajesh Ranganath
60
162
0
08 Mar 2019
A mathematical theory of semantic development in deep neural networks
A mathematical theory of semantic development in deep neural networks
Andrew M. Saxe
James L. McClelland
Surya Ganguli
73
270
0
23 Oct 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
242
8,856
0
25 Aug 2017
Zero-Shot Deep Domain Adaptation
Zero-Shot Deep Domain Adaptation
Kuan-Chuan Peng
Ziyan Wu
Jan Ernst
VLM
71
87
0
06 Jul 2017
Arbitrary Style Transfer in Real-time with Adaptive Instance
  Normalization
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
Xun Huang
Serge J. Belongie
OOD
173
4,349
0
20 Mar 2017
Adversarial Discriminative Domain Adaptation
Adversarial Discriminative Domain Adaptation
Eric Tzeng
Judy Hoffman
Kate Saenko
Trevor Darrell
GAN
OOD
257
4,653
0
17 Feb 2017
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial
  Networks
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
Konstantinos Bousmalis
N. Silberman
David Dohan
D. Erhan
Dilip Krishnan
OOD
GAN
146
1,535
0
16 Dec 2016
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Baochen Sun
Kate Saenko
OOD
91
3,144
0
06 Jul 2016
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
366
9,467
0
28 May 2015
Deep Domain Confusion: Maximizing for Domain Invariance
Deep Domain Confusion: Maximizing for Domain Invariance
Eric Tzeng
Judy Hoffman
Ning Zhang
Kate Saenko
Trevor Darrell
OOD
165
2,598
0
10 Dec 2014
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