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2020 – today
- 2022
[j1]Sean Mann
, Eric Fadel, Samuel S. Schoenholz, Ekin D. Cubuk, Steven G. Johnson, Giuseppe Romano:
∂PV: An end-to-end differentiable solar-cell simulator. Comput. Phys. Commun. 272: 108232 (2022)- [c28]Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov:
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. ICLR 2022 - [c27]Raphael Gontijo Lopes, Yann Dauphin, Ekin Dogus Cubuk:
No One Representation to Rule Them All: Overlapping Features of Training Methods. ICLR 2022 - [c26]Gary Wang, Ekin D. Cubuk, Andrew Rosenberg, Shuyang Cheng, Ron J. Weiss, Bhuvana Ramabhadran, Pedro J. Moreno, Quoc V. Le, Daniel S. Park:
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. SLT 2022: 23-30 - [i30]Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin D. Cubuk:
On the surprising tradeoff between ImageNet accuracy and perceptual similarity. CoRR abs/2203.04946 (2022) - [i29]Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Xiaojie Shi, Shuyang Cheng, Dragomir Anguelov:
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. CoRR abs/2204.12511 (2022) - [i28]Stanislav Fort, Ekin Dogus Cubuk, Surya Ganguli, Samuel S. Schoenholz:
What does a deep neural network confidently perceive? The effective dimension of high certainty class manifolds and their low confidence boundaries. CoRR abs/2210.05546 (2022) - [i27]Gary Wang, Ekin D. Cubuk, Andrew Rosenberg, Shuyang Cheng, Ron J. Weiss, Bhuvana Ramabhadran, Pedro J. Moreno, Quoc V. Le, Daniel S. Park:
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. CoRR abs/2210.10879 (2022) - [i26]Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan:
LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations. CoRR abs/2210.13488 (2022) - 2021
- [c25]Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph:
Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation. CVPR 2021: 2918-2928 - [c24]Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin:
Multi-Task Self-Training for Learning General Representations. ICCV 2021: 8836-8845 - [c23]Yann Dauphin, Ekin Dogus Cubuk:
Deconstructing the Regularization of BatchNorm. ICLR 2021 - [c22]Raphael Gontijo Lopes, Sylvia J. Smullin, Ekin Dogus Cubuk, Ethan Dyer:
Tradeoffs in Data Augmentation: An Empirical Study. ICLR 2021 - [c21]Amil Merchant, Luke Metz, Samuel S. Schoenholz, Ekin D. Cubuk:
Learn2Hop: Learned Optimization on Rough Landscapes. ICML 2021: 7643-7653 - [c20]Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. NeurIPS 2021: 22614-22627 - [i25]Irwan Bello, William Fedus, Xianzhi Du, Ekin D. Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. CoRR abs/2103.07579 (2021) - [i24]Amil Merchant, Luke Metz, Samuel S. Schoenholz, Ekin Dogus Cubuk:
Learn2Hop: Learned Optimization on Rough Landscapes. CoRR abs/2107.09661 (2021) - [i23]Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin:
Multi-Task Self-Training for Learning General Representations. CoRR abs/2108.11353 (2021) - [i22]Raphael Gontijo Lopes, Yann Dauphin, Ekin D. Cubuk:
No One Representation to Rule Them All: Overlapping Features of Training Methods. CoRR abs/2110.12899 (2021) - 2020
- [c19]Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le:
Randaugment: Practical automated data augmentation with a reduced search space. CVPR Workshops 2020: 3008-3017 - [c18]Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov:
Improving 3D Object Detection Through Progressive Population Based Augmentation. ECCV (21) 2020: 279-294 - [c17]Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le:
Learning Data Augmentation Strategies for Object Detection. ECCV (27) 2020: 566-583 - [c16]Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, Jonathon Shlens:
Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. ECCV (9) 2020: 695-714 - [c15]David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel:
ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring. ICLR 2020 - [c14]Dan Hendrycks, Norman Mu, Ekin Dogus Cubuk, Barret Zoph, Justin Gilmer, Balaji Lakshminarayanan:
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty. ICLR 2020 - [c13]Ekin Dogus Cubuk, Barret Zoph, Jonathon Shlens, Quoc Le:
RandAugment: Practical Automated Data Augmentation with a Reduced Search Space. NeurIPS 2020 - [c12]Samuel S. Schoenholz, Ekin Dogus Cubuk:
JAX MD: A Framework for Differentiable Physics. NeurIPS 2020 - [c11]Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li:
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. NeurIPS 2020 - [c10]Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin Dogus Cubuk, Quoc Le:
Rethinking Pre-training and Self-training. NeurIPS 2020 - [i21]Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, Colin Raffel:
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. CoRR abs/2001.07685 (2020) - [i20]Raphael Gontijo Lopes, Sylvia J. Smullin, Ekin D. Cubuk, Ethan Dyer:
Affinity and Diversity: Quantifying Mechanisms of Data Augmentation. CoRR abs/2002.08973 (2020) - [i19]Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov:
Improving 3D Object Detection through Progressive Population Based Augmentation. CoRR abs/2004.00831 (2020) - [i18]Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, Jonathon Shlens:
Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. CoRR abs/2005.10266 (2020) - [i17]Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin D. Cubuk, Quoc V. Le:
Rethinking Pre-training and Self-training. CoRR abs/2006.06882 (2020) - [i16]Li Li, Stephan Hoyer, Ryan Pederson, Ruoxi Sun, Ekin D. Cubuk, Patrick Riley, Kieron Burke:
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics. CoRR abs/2009.08551 (2020) - [i15]Amil Merchant, Barret Zoph, Ekin Dogus Cubuk:
Does Data Augmentation Benefit from Split BatchNorms. CoRR abs/2010.07810 (2020) - [i14]Gowoon Cheon, Lusann Yang, Kevin McCloskey, Evan J. Reed, Ekin D. Cubuk:
Crystal Structure Search with Random Relaxations Using Graph Networks. CoRR abs/2012.02920 (2020) - [i13]Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph:
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation. CoRR abs/2012.07177 (2020)
2010 – 2019
- 2019
- [c9]Ekin D. Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, Quoc V. Le:
AutoAugment: Learning Augmentation Strategies From Data. CVPR 2019: 113-123 - [c8]Justin Gilmer, Nicolas Ford, Nicholas Carlini, Ekin D. Cubuk:
Adversarial Examples Are a Natural Consequence of Test Error in Noise. ICML 2019: 2280-2289 - [c7]Daniel S. Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D. Cubuk, Quoc V. Le:
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition. INTERSPEECH 2019: 2613-2617 - [c6]Dong Yin, Raphael Gontijo Lopes, Jonathon Shlens, Ekin Dogus Cubuk, Justin Gilmer:
A Fourier Perspective on Model Robustness in Computer Vision. NeurIPS 2019: 13255-13265 - [i12]Nic Ford, Justin Gilmer, Nicholas Carlini, Ekin Dogus Cubuk:
Adversarial Examples Are a Natural Consequence of Test Error in Noise. CoRR abs/1901.10513 (2019) - [i11]Daniel S. Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D. Cubuk, Quoc V. Le:
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition. CoRR abs/1904.08779 (2019) - [i10]Raphael Gontijo Lopes, Dong Yin, Ben Poole, Justin Gilmer, Ekin D. Cubuk:
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation. CoRR abs/1906.02611 (2019) - [i9]Luke Metz, Niru Maheswaranathan, Jonathon Shlens, Jascha Sohl-Dickstein, Ekin D. Cubuk:
Using learned optimizers to make models robust to input noise. CoRR abs/1906.03367 (2019) - [i8]Dong Yin, Raphael Gontijo Lopes, Jonathon Shlens, Ekin D. Cubuk, Justin Gilmer:
A Fourier Perspective on Model Robustness in Computer Vision. CoRR abs/1906.08988 (2019) - [i7]Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le:
Learning Data Augmentation Strategies for Object Detection. CoRR abs/1906.11172 (2019) - [i6]Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le:
RandAugment: Practical data augmentation with no separate search. CoRR abs/1909.13719 (2019) - [i5]David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel:
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring. CoRR abs/1911.09785 (2019) - [i4]Dan Hendrycks, Norman Mu, Ekin D. Cubuk, Barret Zoph, Justin Gilmer, Balaji Lakshminarayanan:
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty. CoRR abs/1912.02781 (2019) - 2018
- [c5]Ekin Dogus Cubuk, Barret Zoph, Samuel S. Schoenholz, Quoc V. Le:
Intriguing Properties of Adversarial Examples. ICLR (Workshop) 2018 - [c4]Avital Oliver, Augustus Odena, Colin Raffel, Ekin D. Cubuk, Ian J. Goodfellow:
Realistic Evaluation of Semi-Supervised Learning Algorithms. ICLR (Workshop) 2018 - [c3]Avital Oliver, Augustus Odena, Colin Raffel, Ekin Dogus Cubuk, Ian J. Goodfellow:
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms. NeurIPS 2018: 3239-3250 - [i3]Avital Oliver, Augustus Odena, Colin Raffel, Ekin D. Cubuk, Ian J. Goodfellow:
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms. CoRR abs/1804.09170 (2018) - [i2]Ekin Dogus Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, Quoc V. Le:
AutoAugment: Learning Augmentation Policies from Data. CoRR abs/1805.09501 (2018) - 2017
- [i1]Ekin Dogus Cubuk, Barret Zoph, Samuel S. Schoenholz, Quoc V. Le:
Intriguing Properties of Adversarial Examples. CoRR abs/1711.02846 (2017) - 2013
- [c2]Amos Waterland, Elaine Angelino, Ekin D. Cubuk, Efthimios Kaxiras, Ryan P. Adams, Jonathan Appavoo, Margo I. Seltzer:
Computational caches. SYSTOR 2013: 8:1-8:7
2000 – 2009
- 2009
- [c1]M. Ani Hsieh, Ádám M. Halász, Ekin Dogus Cubuk, Samuel S. Schoenholz, Alcherio Martinoli:
Specialization as an optimal strategy under varying external conditions. ICRA 2009: 1941-1946
Coauthor Index
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last updated on 2023-02-07 22:44 CET by the dblp team
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