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Rishabh Singh

Microsoft Research, Redmond

Deep Geospatial Interpolation Networks


Aug 15, 2021
Sumit Kumar Varshney, Jeetu Kumar, Aditya Tiwari, Rishabh Singh, Venkata M. V. Gunturi, Narayanan C. Krishnan


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SpreadsheetCoder: Formula Prediction from Semi-structured Context


Jun 26, 2021
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou

* Published in ICML 2021 

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Image to Image Translation : Generating maps from satellite images


May 19, 2021
Vaishali Ingale, Rishabh Singh, Pragati Patwal


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A Kernel Framework to Quantify a Model's Local Predictive Uncertainty under Data Distributional Shifts


Mar 02, 2021
Rishabh Singh, Jose C. Principe


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Latent Programmer: Discrete Latent Codes for Program Synthesis


Dec 01, 2020
Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer

* 15 pages, 9 figures 

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Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration


Nov 10, 2020
Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans

* NeurIPS 2020 

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Deep Learning & Software Engineering: State of Research and Future Directions


Sep 17, 2020
Prem Devanbu, Matthew Dwyer, Sebastian Elbaum, Michael Lowry, Kevin Moran, Denys Poshyvanyk, Baishakhi Ray, Rishabh Singh, Xiangyu Zhang

* Community Report from the 2019 NSF Workshop on Deep Learning & Software Engineering, 37 pages 

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BUSTLE: Bottom-up program-Synthesis Through Learning-guided Exploration


Jul 28, 2020
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton


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Scaling Symbolic Methods using Gradients for Neural Model Explanation


Jun 29, 2020
Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley


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Neural Program Synthesis with a Differentiable Fixer


Jun 19, 2020
Matej Balog, Rishabh Singh, Petros Maniatis, Charles Sutton


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TF-Coder: Program Synthesis for Tensor Manipulations


Mar 19, 2020
Kensen Shi, David Bieber, Rishabh Singh


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Towards Modular Algorithm Induction


Feb 27, 2020
Daniel A. Abolafia, Rishabh Singh, Manzil Zaheer, Charles Sutton

* 10 pages, 4 figures, 2 tables 

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Towards a Kernel based Physical Interpretation of Model Uncertainty


Feb 21, 2020
Rishabh Singh, Jose C. Principe


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Synthetic Datasets for Neural Program Synthesis


Dec 27, 2019
Richard Shin, Neel Kant, Kavi Gupta, Christopher Bender, Brandon Trabucco, Rishabh Singh, Dawn Song

* ICLR 2019 

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Learning Transferable Graph Exploration


Oct 28, 2019
Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli

* To appear in NeurIPS 2019 

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MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees


Jun 16, 2019
Marko Vasic, Andrija Petrovic, Kaiyuan Wang, Mladen Nikolic, Rishabh Singh, Sarfraz Khurshid


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Neural Program Repair by Jointly Learning to Localize and Repair


Apr 03, 2019
Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh

* ICLR 2019 

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Neural-Guided Symbolic Regression with Semantic Prior


Jan 23, 2019
Li Li, Minjie Fan, Rishabh Singh, Patrick Riley


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Robust Text-to-SQL Generation with Execution-Guided Decoding


Sep 13, 2018
Chenglong Wang, Kedar Tatwawadi, Marc Brockschmidt, Po-Sen Huang, Yi Mao, Oleksandr Polozov, Rishabh Singh


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Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections


Aug 30, 2018
Xin Zhang, Armando Solar-Lezama, Rishabh Singh

* 24 pages 

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Natural Language to Structured Query Generation via Meta-Learning


Jul 18, 2018
Po-Sen Huang, Chenglong Wang, Rishabh Singh, Wen-tau Yih, Xiaodong He

* in NAACL HLT 2018 

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Towards Mixed Optimization for Reinforcement Learning with Program Synthesis


Jul 03, 2018
Surya Bhupatiraju, Kumar Krishna Agrawal, Rishabh Singh

* Updated publication details, format. Accepted at NAMPI workshop, ICML '18 

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Dynamic Neural Program Embedding for Program Repair


Jun 30, 2018
Ke Wang, Rishabh Singh, Zhendong Su

* 9 pages 

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Programmatically Interpretable Reinforcement Learning


Jun 08, 2018
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri

* Accepted by The 35th International Conference on Machine Learning (ICML 2018) 

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Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis


May 22, 2018
Rudy Bunel, Matthew Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli

* ICLR 2018 

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Learning and analyzing vector encoding of symbolic representations


Mar 10, 2018
Roland Fernandez, Asli Celikyilmaz, Rishabh Singh, Paul Smolensky


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Deep Reinforcement Fuzzing


Jan 14, 2018
Konstantin Böttinger, Patrice Godefroid, Rishabh Singh


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SyGuS-Comp 2017: Results and Analysis


Nov 29, 2017
Rajeev Alur, Dana Fisman, Rishabh Singh, Armando Solar-Lezama

* EPTCS 260, 2017, pp. 97-115 
* In Proceedings SYNT 2017, arXiv:1711.10224. arXiv admin note: text overlap with arXiv:1611.07627, arXiv:1602.01170 

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Not all bytes are equal: Neural byte sieve for fuzzing


Nov 10, 2017
Mohit Rajpal, William Blum, Rishabh Singh


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