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2020 – today
- 2022
[i13]Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals:
Competition-Level Code Generation with AlphaCode. CoRR abs/2203.07814 (2022)- [i12]Jonathan Uesato, Nate Kushman, Ramana Kumar, H. Francis Song, Noah Y. Siegel, Lisa Wang, Antonia Creswell, Geoffrey Irving, Irina Higgins:
Solving math word problems with process- and outcome-based feedback. CoRR abs/2211.14275 (2022) - 2020
- [c19]Marco Federici, Anjan Dutta, Patrick Forré, Nate Kushman, Zeynep Akata:
Learning Robust Representations via Multi-View Information Bottleneck. ICLR 2020 - [i11]Marco Federici, Anjan Dutta, Patrick Forré, Nate Kushman, Zeynep Akata:
Learning Robust Representations via Multi-View Information Bottleneck. CoRR abs/2002.07017 (2020) - [i10]Sebastian Lunz, Yingzhen Li, Andrew W. Fitzgibbon, Nate Kushman:
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data. CoRR abs/2002.12674 (2020) - [i9]Chaochao Lu, Richard E. Turner, Yingzhen Li, Nate Kushman:
Interpreting Spatially Infinite Generative Models. CoRR abs/2007.12411 (2020)
2010 – 2019
- 2019
- [c18]Charlie Nash, Nate Kushman, Christopher K. I. Williams:
Inverting Supervised Representations with Autoregressive Neural Density Models. AISTATS 2019: 1620-1629 - 2018
- [c17]Arianna Yuan, Will Monroe, Yu Bai, Nate Kushman:
Understanding the Rational Speech Act model. CogSci 2018 - [c16]Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman:
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. ICLR (Poster) 2018 - [c15]Yang Song, Rui Shu, Nate Kushman, Stefano Ermon:
Constructing Unrestricted Adversarial Examples with Generative Models. NeurIPS 2018: 8322-8333 - [i8]Yang Song, Rui Shu, Nate Kushman, Stefano Ermon:
Generative Adversarial Examples. CoRR abs/1805.07894 (2018) - [i7]Charlie Nash, Nate Kushman, Christopher K. I. Williams:
Inverting Supervised Representations with Autoregressive Neural Density Models. CoRR abs/1806.00400 (2018) - 2017
- [c14]Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow:
Lifelong Perceptual Programming By Example. ICLR (Workshop) 2017 - [c13]Chengtao Li, Daniel Tarlow, Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman:
Neural Program Lattices. ICLR (Poster) 2017 - [c12]Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow:
Differentiable Programs with Neural Libraries. ICML 2017: 1213-1222 - [i6]Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman:
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. CoRR abs/1710.10766 (2017) - 2016
- [c11]Nicholas Locascio, Karthik Narasimhan, Eduardo DeLeon, Nate Kushman, Regina Barzilay:
Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge. EMNLP 2016: 1918-1923 - [c10]Rik Koncel-Kedziorski, Subhro Roy, Aida Amini, Nate Kushman, Hannaneh Hajishirzi:
MAWPS: A Math Word Problem Repository. HLT-NAACL 2016: 1152-1157 - [i5]Nicholas Locascio, Karthik Narasimhan, Eduardo DeLeon, Nate Kushman, Regina Barzilay:
Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge. CoRR abs/1608.03000 (2016) - [i4]Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, Daniel Tarlow:
TerpreT: A Probabilistic Programming Language for Program Induction. CoRR abs/1608.04428 (2016) - [i3]Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow:
Lifelong Perceptual Programming By Example. CoRR abs/1611.02109 (2016) - [i2]Felix Leibfried, Nate Kushman, Katja Hofmann:
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games. CoRR abs/1611.07078 (2016) - [i1]Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, Daniel Tarlow:
Summary - TerpreT: A Probabilistic Programming Language for Program Induction. CoRR abs/1612.00817 (2016) - 2015
- [b1]Nate Kushman:
Generating computer programs from natural language descriptions. Massachusetts Institute of Technology, Cambridge, MA, USA, 2015 - 2014
- [c9]Nate Kushman, Luke Zettlemoyer, Regina Barzilay, Yoav Artzi:
Learning to Automatically Solve Algebra Word Problems. ACL (1) 2014: 271-281 - [c8]Mohammad Javad Hosseini, Hannaneh Hajishirzi, Oren Etzioni, Nate Kushman:
Learning to Solve Arithmetic Word Problems with Verb Categorization. EMNLP 2014: 523-533 - 2013
- [c7]Nate Kushman, Regina Barzilay:
Using Semantic Unification to Generate Regular Expressions from Natural Language. HLT-NAACL 2013: 826-836 - 2012
- [c6]S. R. K. Branavan, Nate Kushman, Tao Lei, Regina Barzilay:
Learning High-Level Planning from Text. ACL (1) 2012: 126-135 - 2010
- [c5]Nate Kushman, Dina Katabi:
Enabling Configuration-Independent Automation by Non-Expert Users. OSDI 2010: 223-236
2000 – 2009
- 2009
- [c4]Nate Kushman, Micah Z. Brodsky, S. R. K. Branavan, Dina Katabi, Regina Barzilay, Martin C. Rinard:
WikiDo. HotNets 2009 - 2008
- [c3]Kate Ching-Ju Lin, Nate Kushman, Dina Katabi:
ZipTx: exploiting the gap between bit errors and packet loss. MobiCom 2008: 351-362 - [c2]Hariharan Rahul, Nate Kushman, Dina Katabi, Charles G. Sodini, Farinaz Edalat:
Learning to share: narrowband-friendly wideband networks. SIGCOMM 2008: 147-158 - 2007
- [j1]Nate Kushman, Srikanth Kandula, Dina Katabi:
Can you hear me now?!: it must be BGP. Comput. Commun. Rev. 37(2): 75-84 (2007) - [c1]Nate Kushman, Srikanth Kandula, Dina Katabi, Bruce M. Maggs:
R-BGP: Staying Connected in a Connected World. NSDI 2007
Coauthor Index
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