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Techniques for Symbol Grounding with SATNet


Jun 16, 2021
Sever Topan, David Rolnick, Xujie Si

* Code available at https://github.com/SeverTopan/SATNet 

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DC3: A learning method for optimization with hard constraints


Apr 25, 2021
Priya L. Donti, David Rolnick, J. Zico Kolter

* International Conference on Learning Representations 2021 
* In ICLR 2021. Code available at https://github.com/locuslab/DC3 

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Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification


Mar 21, 2021
Charles A. Kantor, Marta Skreta, Brice Rauby, Léonard Boussioux, Emmanuel Jehanno, Alexandra Luccioni, David Rolnick, Hugues Talbot

* Proc. IJCAI 2021, Workshop on AI for Social Good, Harvard University (2021) 
* Copyright by the authors. All rights reserved to authors only. Correspondence to: ckantor (at) stanford [dot] edu 

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Deep ReLU Networks Preserve Expected Length


Feb 21, 2021
Boris Hanin, Ryan Jeong, David Rolnick

* 25 pages, 5 figures 

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Identifying Weights and Architectures of Unknown ReLU Networks


Oct 02, 2019
David Rolnick, Konrad P. Kording

* 15 pages, 4 figures 

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Tackling Climate Change with Machine Learning


Jun 10, 2019
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio


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Deep ReLU Networks Have Surprisingly Few Activation Patterns


Jun 03, 2019
Boris Hanin, David Rolnick

* 18 page, 7 figures 

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Complexity of Linear Regions in Deep Networks


Jan 25, 2019
Boris Hanin, David Rolnick


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Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics


Dec 04, 2018
Yaron Meirovitch, Lu Mi, Hayk Saribekyan, Alexander Matveev, David Rolnick, Casimir Wierzynski, Nir Shavit

* 10 pages, 10 figures 

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Experience Replay for Continual Learning


Nov 28, 2018
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, Greg Wayne


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How to Start Training: The Effect of Initialization and Architecture


Jun 19, 2018
Boris Hanin, David Rolnick

* v2. 15p. Comments welcome 

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Measuring and regularizing networks in function space


May 21, 2018
Ari S. Benjamin, David Rolnick, Konrad Kording

* Submitted to to NIPS 2018 

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The power of deeper networks for expressing natural functions


Apr 27, 2018
David Rolnick, Max Tegmark

* Replaced to match version published at ICLR 2018. 14 pages, 2 figs 

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Deep Learning is Robust to Massive Label Noise


Feb 26, 2018
David Rolnick, Andreas Veit, Serge Belongie, Nir Shavit


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Why does deep and cheap learning work so well?


Aug 03, 2017
Henry W. Lin, Max Tegmark, David Rolnick

* Replaced to match version published in Journal of Statistical Physics: https://link.springer.com/article/10.1007/s10955-017-1836-5 Improved refs & discussion, typos fixed. 16 pages, 3 figs 

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Morphological Error Detection in 3D Segmentations


May 30, 2017
David Rolnick, Yaron Meirovitch, Toufiq Parag, Hanspeter Pfister, Viren Jain, Jeff W. Lichtman, Edward S. Boyden, Nir Shavit

* 13 pages, 6 figures 

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A Multi-Pass Approach to Large-Scale Connectomics


Dec 07, 2016
Yaron Meirovitch, Alexander Matveev, Hayk Saribekyan, David Budden, David Rolnick, Gergely Odor, Seymour Knowles-Barley, Thouis Raymond Jones, Hanspeter Pfister, Jeff William Lichtman, Nir Shavit

* 18 pages, 10 figures 

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