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Maithra Raghu
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2020 – today
- 2022
- [j2]Thao Nguyen, Maithra Raghu, Simon Kornblith:
On the Origins of the Block Structure Phenomenon in Neural Network Representations. Trans. Mach. Learn. Res. 2022 (2022) - [c18]Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang:
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures. NeurIPS 2022 - [i21]Thao Nguyen, Maithra Raghu, Simon Kornblith:
On the Origins of the Block Structure Phenomenon in Neural Network Representations. CoRR abs/2202.07184 (2022) - [i20]Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang:
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures. CoRR abs/2205.13647 (2022) - 2021
- [c17]Thao Nguyen, Maithra Raghu, Simon Kornblith:
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth. ICLR 2021 - [c16]Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton:
Teaching with Commentaries. ICLR 2021 - [c15]Vinay Venkatesh Ramasesh, Ethan Dyer, Maithra Raghu:
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics. ICLR 2021 - [c14]Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy:
Do Vision Transformers See Like Convolutional Neural Networks? NeurIPS 2021: 12116-12128 - [i19]Chiyuan Zhang, Maithra Raghu, Jon M. Kleinberg, Samy Bengio:
Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization. CoRR abs/2107.12580 (2021) - [i18]Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy:
Do Vision Transformers See Like Convolutional Neural Networks? CoRR abs/2108.08810 (2021) - 2020
- [c13]Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals:
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML. ICLR 2020 - [i17]Maithra Raghu, Eric Schmidt:
A Survey of Deep Learning for Scientific Discovery. CoRR abs/2003.11755 (2020) - [i16]Vinay V. Ramasesh, Ethan Dyer, Maithra Raghu:
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics. CoRR abs/2007.07400 (2020) - [i15]Thao Nguyen, Maithra Raghu, Simon Kornblith:
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth. CoRR abs/2010.15327 (2020) - [i14]Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton:
Teaching with Commentaries. CoRR abs/2011.03037 (2020)
2010 – 2019
- 2019
- [c12]Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Robert D. Kleinberg, Sendhil Mullainathan, Jon M. Kleinberg:
Direct Uncertainty Prediction for Medical Second Opinions. ICML 2019: 5281-5290 - [c11]Maithra Raghu, Chiyuan Zhang, Jon M. Kleinberg, Samy Bengio:
Transfusion: Understanding Transfer Learning for Medical Imaging. NeurIPS 2019: 3342-3352 - [i13]Maithra Raghu, Chiyuan Zhang, Jon M. Kleinberg, Samy Bengio:
Transfusion: Understanding Transfer Learning with Applications to Medical Imaging. CoRR abs/1902.07208 (2019) - [i12]Maithra Raghu, Katy Blumer, Greg Corrado, Jon M. Kleinberg, Ziad Obermeyer, Sendhil Mullainathan:
The Algorithmic Automation Problem: Prediction, Triage, and Human Effort. CoRR abs/1903.12220 (2019) - [i11]Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals:
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML. CoRR abs/1909.09157 (2019) - 2018
- [j1]Jon M. Kleinberg, Maithra Raghu:
Team Performance with Test Scores. ACM Trans. Economics and Comput. 6(3-4): 17:1-17:26 (2018) - [c10]Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow:
Adversarial Spheres. ICLR (Workshop) 2018 - [c9]Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg:
Can Deep Reinforcement Learning solve Erdos-Selfridge-Spencer Games? ICLR (Workshop) 2018 - [c8]Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg:
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? ICML 2018: 4235-4243 - [c7]Ari S. Morcos, Maithra Raghu, Samy Bengio:
Insights on representational similarity in neural networks with canonical correlation. NeurIPS 2018: 5732-5741 - [i10]Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow:
Adversarial Spheres. CoRR abs/1801.02774 (2018) - [i9]Ari S. Morcos, Maithra Raghu, Samy Bengio:
Insights on representational similarity in neural networks with canonical correlation. CoRR abs/1806.05759 (2018) - [i8]Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Sendhil Mullainathan, Jon M. Kleinberg:
Direct Uncertainty Prediction with Applications to Healthcare. CoRR abs/1807.01771 (2018) - 2017
- [c6]Justin Gilmer, Colin Raffel, Samuel S. Schoenholz, Maithra Raghu, Jascha Sohl-Dickstein:
Explaining the Learning Dynamics of Direct Feedback Alignment. ICLR (Workshop) 2017 - [c5]Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein:
On the Expressive Power of Deep Neural Networks. ICML 2017: 2847-2854 - [c4]Maithra Raghu, Justin Gilmer, Jason Yosinski, Jascha Sohl-Dickstein:
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability. NIPS 2017: 6076-6085 - [c3]Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins:
Linear Additive Markov Processes. WWW 2017: 411-419 - [i7]Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins:
Linear Additive Markov Processes. CoRR abs/1704.01255 (2017) - [i6]Maithra Raghu, Justin Gilmer, Jason Yosinski, Jascha Sohl-Dickstein:
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Understanding and Improvement. CoRR abs/1706.05806 (2017) - [i5]Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg:
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? CoRR abs/1711.02301 (2017) - 2016
- [c2]Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli:
Exponential expressivity in deep neural networks through transient chaos. NIPS 2016: 3360-3368 - [i4]Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein:
On the expressive power of deep neural networks. CoRR abs/1606.05336 (2016) - [i3]Ben Poole, Subhaneil Lahiri
, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli:
Exponential expressivity in deep neural networks through transient chaos. CoRR abs/1606.05340 (2016) - [i2]Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein:
Survey of Expressivity in Deep Neural Networks. CoRR abs/1611.08083 (2016) - 2015
- [c1]Jon M. Kleinberg, Maithra Raghu:
Team Performance with Test Scores. EC 2015: 511-528 - [i1]Jon M. Kleinberg, Maithra Raghu:
Team Performance with Test Scores. CoRR abs/1506.00147 (2015)
Coauthor Index
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