R-BGP: Staying Connected in a Connected World. - Nate Kushman; Srikanth Kandula; Dina Katabi; Bruce M. Maggs (NSDI, 2007)

Can you hear me now?!: it must be BGP. - Nate Kushman; Srikanth Kandula; Dina Katabi (Comput. Commun. Rev., 2007)

ZipTx: exploiting the gap between bit errors and packet loss. - Kate Ching-Ju Lin; Nate Kushman; Dina Katabi (MobiCom, 2008)

Learning to share: narrowband-friendly wideband networks. - Hariharan Rahul; Nate Kushman; Dina Katabi; Charles G. Sodini; Farinaz Edalat (SIGCOMM, 2008)

WikiDo. - Nate Kushman; Micah Z. Brodsky; S. R. K. Branavan; Dina Katabi; Regina Barzilay; Martin C. Rinard (HotNets, 2009)

Enabling Configuration-Independent Automation by Non-Expert Users. - Nate Kushman; Dina Katabi (OSDI, 2010)

Learning High-Level Planning from Text. - S. R. K. Branavan; Nate Kushman; Tao Lei 001; Regina Barzilay (ACL (1), 2012)

Using Semantic Unification to Generate Regular Expressions from Natural Language. - Nate Kushman; Regina Barzilay (HLT-NAACL, 2013)

Learning to Automatically Solve Algebra Word Problems. - Nate Kushman; Luke Zettlemoyer; Regina Barzilay; Yoav Artzi (ACL (1), 2014)

Learning to Solve Arithmetic Word Problems with Verb Categorization. - Mohammad Javad Hosseini; Hannaneh Hajishirzi; Oren Etzioni; Nate Kushman (EMNLP, 2014)

Generating computer programs from natural language descriptions. - Nate Kushman (2015)

Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge. - Nicholas Locascio; Karthik Narasimhan; Eduardo DeLeon; Nate Kushman; Regina Barzilay (EMNLP, 2016)

MAWPS: A Math Word Problem Repository. - Rik Koncel-Kedziorski; Subhro Roy; Aida Amini; Nate Kushman; Hannaneh Hajishirzi (HLT-NAACL, 2016)

TerpreT: A Probabilistic Programming Language for Program Induction. - Alexander L. Gaunt; Marc Brockschmidt; Rishabh Singh; Nate Kushman; Pushmeet Kohli; Jonathan Taylor 001; Daniel Tarlow (CoRR, 2016)

Summary - TerpreT: A Probabilistic Programming Language for Program Induction. - Alexander L. Gaunt; Marc Brockschmidt; Rishabh Singh; Nate Kushman; Pushmeet Kohli; Jonathan Taylor 001; Daniel Tarlow (CoRR, 2016)

A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games. - Felix Leibfried; Nate Kushman; Katja Hofmann (CoRR, 2016)

Lifelong Perceptual Programming By Example. - Alexander L. Gaunt; Marc Brockschmidt; Nate Kushman; Daniel Tarlow (ICLR (Workshop), 2017)

Neural Program Lattices. - Chengtao Li; Daniel Tarlow; Alexander L. Gaunt; Marc Brockschmidt; Nate Kushman (ICLR (Poster), 2017)

Differentiable Programs with Neural Libraries. - Alexander L. Gaunt; Marc Brockschmidt; Nate Kushman; Daniel Tarlow (ICML, 2017)

Understanding the Rational Speech Act model. - Arianna Yuan; Will Monroe; Yu Bai; Nate Kushman (CogSci, 2018)

PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. - Yang Song 011; Taesup Kim; Sebastian Nowozin; Stefano Ermon; Nate Kushman (ICLR (Poster), 2018)

Constructing Unrestricted Adversarial Examples with Generative Models. - Yang Song 011; Rui Shu; Nate Kushman; Stefano Ermon (NeurIPS, 2018)

Generative Adversarial Examples. - Yang Song 011; Rui Shu; Nate Kushman; Stefano Ermon (CoRR, 2018)

Inverting Supervised Representations with Autoregressive Neural Density Models. - Charlie Nash; Nate Kushman; Christopher K. I. Williams (AISTATS, 2019)

Learning Robust Representations via Multi-View Information Bottleneck. - Marco Federici; Anjan Dutta 001; Patrick Forré; Nate Kushman; Zeynep Akata (ICLR, 2020)

Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data. - Sebastian Lunz; Yingzhen Li; Andrew W. Fitzgibbon; Nate Kushman (CoRR, 2020)

Interpreting Spatially Infinite Generative Models. - Chaochao Lu; Richard E. Turner; Yingzhen Li; Nate Kushman (CoRR, 2020)

Competition-Level Code Generation with AlphaCode. - Yujia Li 001; David H. Choi; Junyoung Chung; Nate Kushman; Julian Schrittwieser; Rémi Leblond; Tom Eccles; James Keeling; Felix Gimeno; Agustin Dal Lago; Thomas Hubert; Peter Choy; et al. (CoRR, 2022)

Solving math word problems with process- and outcome-based feedback. - Jonathan Uesato; Nate Kushman; Ramana Kumar; H. Francis Song; Noah Y. Siegel; Lisa Wang; Antonia Creswell; Geoffrey Irving; Irina Higgins (CoRR, 2022)