Rishabh Singh

ORCID

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 115

Top Venues

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Gabriel Orlanski, Kefan Xiao, Xavier Garcia, Jeffrey Hui, Joshua Howland, Jonathan Malmaud, Jacob Austin, Rishabh Singh, Michele Catasta
Measuring the Impact of Programming Language Distribution. ICML (2023)
Rishabh Singh, José C. Príncipe
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS. CoRR (2022)
Kavita Pabreja, Anubhuti Singh, Rishabh Singh, Rishita Agnihotri, Shriam Kaushik, Tanvi Malhotra
Prediction of Stress Level on Indian Working Professionals Using Machine Learning. Int. J. Hum. Cap. Inf. Technol. Prof. 13 (1) (2022)
Murtadha D. Hssayeni, Arash Andalib, Rishabh Singh, Diego Pava, Kan Li, Steven Borzak, Robert Chait, Kaustubh Kale
ECG Fiducial Point Localization Using a Deep Learning Model. ICMLA (2022)
Qinheping Hu, Rishabh Singh, Loris D'Antoni
Solving Program Sketches with Large Integer Values. ACM Trans. Program. Lang. Syst. 44 (2) (2022)
Rishabh Singh, Shirin Goshtasbpour
Platt-Bin: Efficient Posterior Calibrated Training for NLP Classifiers. ACL (Findings) (2022)
Kensen Shi, David Bieber, Rishabh Singh
TF-Coder: Program Synthesis for Tensor Manipulations. ACM Trans. Program. Lang. Syst. 44 (2) (2022)
Rishabh Singh, José C. Príncipe
Robust Dependence Measure using RKHS based Uncertainty Moments and Optimal Transport. CoRR (2022)
Marko Vasic, Andrija Petrovic, Kaiyuan Wang, Mladen Nikolic, Rishabh Singh, Sarfraz Khurshid
MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning. Neural Networks 151 (2022)
Vaishali Ingale, Rishabh Singh, Pragati Patwal
Image to Image Translation : Generating maps from satellite images. CoRR (2021)
Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley
Scaling Symbolic Methods using Gradients for Neural Model Explanation. ICLR (2021)
Shobha Vasudevan, Wenjie Jiang, David Bieber, Rishabh Singh, Hamid Shojaei, Richard Ho, Charles Sutton
Learning Semantic Representations to Verify Hardware Designs. NeurIPS (2021)
Rishabh Singh, José C. Príncipe
A Kernel Framework to Quantify a Model's Local Predictive Uncertainty under Data Distributional Shifts. CoRR (2021)
Rishabh Singh
Bias: Bijective Input And Surjectivity In Zero Shot Learning. ICIP (2021)
Rishabh Singh, José C. Príncipe
Toward a Kernel-Based Uncertainty Decomposition Framework for Data and Models. Neural Comput. 33 (5) (2021)
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
SpreadsheetCoder: Formula Prediction from Semi-structured Context. CoRR (2021)
Swarat Chaudhuri, Kevin Ellis, Oleksandr Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yue
Neurosymbolic Programming. Found. Trends Program. Lang. 7 (3) (2021)
Sumit Kumar Varshney, Jeetu Kumar, Aditya Tiwari, Rishabh Singh, Venkata M. V. Gunturi, Narayanan C. Krishnan
Deep Geospatial Interpolation Networks. CoRR (2021)
Rishabh Singh, Devansh Timbadia, Vidhi Kapoor, Rishabh Reddy, Prathamesh P. Churi, Omkar Pimple
Question paper generation through progressive model and difficulty calculation on the Promexa Mobile Application. Educ. Inf. Technol. 26 (4) (2021)
Digvijay Singh, Rishabh Singh, Rahul Ajmeria, Manik Gupta, R. N. Ponnalagu
DAWSSM: A plug-and-play Drone Assisted Water Sampling and Sensing Module. IECON (2021)
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration. ICLR (2021)
Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer
Latent Programmer: Discrete Latent Codes for Program Synthesis. ICML (2021)
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
SpreadsheetCoder: Formula Prediction from Semi-structured Context. ICML (2021)
Rishabh Singh, José C. Príncipe
Quantifying Model Predictive Uncertainty with Perturbation Theory. CoRR (2021)
Dana Fisman, Rishabh Singh, Armando Solar-Lezama
Special Issue on Syntax-Guided Synthesis Preface. Formal Methods Syst. Des. 58 (3) (2021)
Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer
Latent Programmer: Discrete Latent Codes for Program Synthesis. CoRR (2020)
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton
BUSTLE: Bottom-up program-Synthesis Through Learning-guided Exploration. CoRR (2020)
Rishabh Singh, Shujian Yu, José C. Príncipe
Composite Dynamic Texture Synthesis Using Hierarchical Linear Dynamical System. ICASSP (2020)
Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. CoRR (2020)
Daniel A. Abolafia, Rishabh Singh, Manzil Zaheer, Charles Sutton
Towards Modular Algorithm Induction. CoRR (2020)
Rishabh Singh, José C. Príncipe
Towards a Kernel based Physical Interpretation of Model Uncertainty. CoRR (2020)
Matej Balog, Rishabh Singh, Petros Maniatis, Charles Sutton
Neural Program Synthesis with a Differentiable Fixer. CoRR (2020)
Prem Devanbu, Matthew B. Dwyer, Sebastian G. Elbaum, Michael Lowry, Kevin Moran, Denys Poshyvanyk, Baishakhi Ray, Rishabh Singh, Xiangyu Zhang
Deep Learning & Software Engineering: State of Research and Future Directions. CoRR (2020)
Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, David Bieber
Global Relational Models of Source Code. ICLR (2020)
Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. NeurIPS (2020)
Ajay Vikram Singh, Daniel Rosenkranz, Mohammad Hasan Dad Ansari, Rishabh Singh, Anurag Kanase, Shubham Pratap Singh, Blair Johnston, Jutta Tentschert, Peter Laux, Andreas Luch
Artificial Intelligence and Machine Learning Empower Advanced Biomedical Material Design to Toxicity Prediction. Adv. Intell. Syst. 2 (12) (2020)
Shengwei An, Rishabh Singh, Sasa Misailovic, Roopsha Samanta
Augmented example-based synthesis using relational perturbation properties. Proc. ACM Program. Lang. 4 (POPL) (2020)
Kensen Shi, David Bieber, Rishabh Singh
TF-Coder: Program Synthesis for Tensor Manipulations. CoRR (2020)
Rong Pan, Qinheping Hu, Rishabh Singh, Loris D'Antoni
Solving Program Sketches with Large Integer Values. ESOP (2020)
Jiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik
Generating Programmatic Referring Expressions via Program Synthesis. ICML (2020)
Ajay Vikram Singh, Daniel Rosenkranz, Mohammad Hasan Dad Ansari, Rishabh Singh, Anurag Kanase, Shubham Pratap Singh, Blair Johnston, Jutta Tentschert, Peter Laux, Andreas Luch
Artificial Intelligence and Machine Learning Empower Advanced Biomedical Material Design to Toxicity Prediction. Adv. Intell. Syst. 2 (12) (2020)
Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick F. Riley
Scaling Symbolic Methods using Gradients for Neural Model Explanation. CoRR (2020)
Rishabh Reddy, Rishabh Singh, Vidhi Kapoor, Prathamesh P. Churi
Joy of Learning Through Internet Memes. Int. J. Eng. Pedagog. 10 (5) (2020)
Rishabh Reddy, Rishabh Singh, Vidhi Kapoor, Prathamesh P. Churi
Cyberbullying and Indian Society: Outcomes from Social Conclave Conference. ISTAS (2020)
Rishabh Singh, José C. Príncipe
Time Series Analysis using a Kernel based Multi-Modal Uncertainty Decomposition Framework. UAI (2020)
Rajeev Alur, Dana Fisman, Saswat Padhi, Rishabh Singh, Abhishek Udupa
SyGuS-Comp 2018: Results and Analysis. CoRR (2019)
Richard Shin, Neel Kant, Kavi Gupta, Chris Bender, Brandon Trabucco, Rishabh Singh, Dawn Song
Synthetic Datasets for Neural Program Synthesis. ICLR (Poster) (2019)
Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
Learning Transferable Graph Exploration. CoRR (2019)
Qinheping Hu, Roopsha Samanta, Rishabh Singh, Loris D'Antoni
Direct Manipulation for Imperative Programs. SAS (2019)
Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh
Neural Program Repair by Jointly Learning to Localize and Repair. ICLR (Poster) (2019)
Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh
Neural Program Repair by Jointly Learning to Localize and Repair. CoRR (2019)
Abhinav Kumar, Aishwarya Gupta, Bishal Santra, K. S. Lalitha, Manasa Kolla, Mayank Gupta, Rishabh Singh
VPDS: An AI-Based Automated Vehicle Occupancy and Violation Detection System. AAAI (2019)
Li Li, Minjie Fan, Rishabh Singh, Patrick Riley
Neural-Guided Symbolic Regression with Semantic Prior. CoRR (2019)
Marko Vasic, Andrija Petrovic, Kaiyuan Wang, Mladen Nikolic, Rishabh Singh, Sarfraz Khurshid
MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees. CoRR (2019)
Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
Learning Transferable Graph Exploration. NeurIPS (2019)
Richard Shin, Neel Kant, Kavi Gupta, Christopher Bender, Brandon Trabucco, Rishabh Singh, Dawn Song
Synthetic Datasets for Neural Program Synthesis. CoRR (2019)
Qinheping Hu, Isaac Evavold, Roopsha Samanta, Rishabh Singh, Loris D'Antoni
Program Repair via Direct State Manipulation. CoRR (2018)
Ke Wang, Rishabh Singh, Zhendong Su
Search, align, and repair: data-driven feedback generation for introductory programming exercises. PLDI (2018)
Xin Zhang, Armando Solar-Lezama, Rishabh Singh
Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections. CoRR (2018)
Konstantin Böttinger, Patrice Godefroid, Rishabh Singh
Deep Reinforcement Fuzzing. CoRR (2018)
Xinyu Wang, Isil Dillig, Rishabh Singh
Program synthesis using abstraction refinement. Proc. ACM Program. Lang. 2 (POPL) (2018)
Po-Sen Huang, Chenglong Wang, Rishabh Singh, Wen-tau Yih, Xiaodong He
Natural Language to Structured Query Generation via Meta-Learning. CoRR (2018)
Xin Zhang, Armando Solar-Lezama, Rishabh Singh
Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections. NeurIPS (2018)
Po-Sen Huang, Chenglong Wang, Rishabh Singh, Wen-tau Yih, Xiaodong He
Natural Language to Structured Query Generation via Meta-Learning. NAACL-HLT (2) (2018)
Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. ICLR (Poster) (2018)
Sahil Bhatia, Pushmeet Kohli, Rishabh Singh
Neuro-symbolic program corrector for introductory programming assignments. ICSE (2018)
Rishabh Singh, José C. Príncipe
Correntropy Based Hierarchical Linear Dynamical System For Speech Recognition. IJCNN (2018)
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri
Programmatically Interpretable Reinforcement Learning. CoRR (2018)
Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. CoRR (2018)
Chenglong Wang, Po-Sen Huang, Alex Polozov, Marc Brockschmidt, Rishabh Singh
Execution-Guided Neural Program Decoding. CoRR (2018)
Sitara Shah, Snigdha Petluru, Rishabh Singh, Saurabh Srivastava
gAR-age: A Feedback-Enabled Blended Ecosystem for Vehicle Health Monitoring. AutomotiveUI (2018)
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri
Programmatically Interpretable Reinforcement Learning. ICML (2018)
Jeevana Priya Inala, Rishabh Singh
WebRelate: integrating web data with spreadsheets using examples. Proc. ACM Program. Lang. 2 (POPL) (2018)
Rajeev Alur, Rishabh Singh, Dana Fisman, Armando Solar-Lezama
Search-based program synthesis. Commun. ACM 61 (12) (2018)
Konstantin Böttinger, Patrice Godefroid, Rishabh Singh
Deep Reinforcement Fuzzing. IEEE Symposium on Security and Privacy Workshops (2018)
Surya Bhupatiraju, Kumar Krishna Agrawal, Rishabh Singh
Towards Mixed Optimization for Reinforcement Learning with Program Synthesis. CoRR (2018)
Roland Fernandez, Asli Celikyilmaz, Rishabh Singh, Paul Smolensky
Learning and analyzing vector encoding of symbolic representations. CoRR (2018)
Ke Wang, Rishabh Singh, Zhendong Su
Dynamic Neural Program Embeddings for Program Repair. ICLR (Poster) (2018)
Rishabh Singh, Kan Li, José C. Príncipe
Nearest-Instance-Centroid-Estimation Linear Discriminant Analysis (Nice Lda). ICASSP (2018)
Roland Fernandez, Asli Celikyilmaz, Paul Smolensky, Rishabh Singh
Learning and Analyzing Vector Encoding of Symbolic Representation. ICLR (Workshop) (2018)
Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed, Pushmeet Kohli
RobustFill: Neural Program Learning under Noisy I/O. ICML (2017)
Ute Schmid, Stephen H. Muggleton, Rishabh Singh
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382). Dagstuhl Reports 7 (9) (2017)
Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli
Neural Program Meta-Induction. NIPS (2017)
Loris D'Antoni, Rishabh Singh, Michael Vaughn
NoFAQ: synthesizing command repairs from examples. ESEC/SIGSOFT FSE (2017)
Sumit Gulwani, Oleksandr Polozov, Rishabh Singh
Program Synthesis. Found. Trends Program. Lang. 4 (1-2) (2017)
Rajeev Alur, Dana Fisman, Rishabh Singh, Armando Solar-Lezama
SyGuS-Comp 2017: Results and Analysis. SYNT@CAV (2017)
Patrice Godefroid, Hila Peleg, Rishabh Singh
Learn&Fuzz: Machine Learning for Input Fuzzing. CoRR (2017)
Rishabh Singh, Pushmeet Kohli
AP: Artificial Programming. SNAPL (2017)
Jeevana Priya Inala, Rishabh Singh
WebRelate: Integrating Web Data with Spreadsheets using Examples. CoRR (2017)
Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed, Pushmeet Kohli
Deep API Programmer: Learning to Program with APIs. CoRR (2017)
Xinyu Wang, Isil Dillig, Rishabh Singh
Synthesis of data completion scripts using finite tree automata. Proc. ACM Program. Lang. 1 (OOPSLA) (2017)
Vivek Venugopal, Abhishek Sharma, Rishabh Singh, Abhinav Sharma, Suresh Sundaram
A Vector Quantization Based Feature Descriptor for Online Signature Verification. ICDAR (2017)
Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, Pushmeet Kohli
Neuro-Symbolic Program Synthesis. ICLR (Poster) (2017)
Xinyu Wang, Isil Dillig, Rishabh Singh
Synthesis of Data Completion Scripts using Finite Tree Automata. CoRR (2017)
Ke Wang, Benjamin Lin, Bjorn Rettig, Paul Pardi, Rishabh Singh
Data-Driven Feedback Generator for Online Programing Courses. L@S (2017)
Patrice Godefroid, Hila Peleg, Rishabh Singh
Learn&Fuzz: machine learning for input fuzzing. ASE (2017)
Jacob Devlin, Jonathan Uesato, Rishabh Singh, Pushmeet Kohli
Semantic Code Repair using Neuro-Symbolic Transformation Networks. CoRR (2017)
Mohit Rajpal, William Blum, Rishabh Singh
Not all bytes are equal: Neural byte sieve for fuzzing. CoRR (2017)
Ke Wang, Rishabh Singh, Zhendong Su
Dynamic Neural Program Embedding for Program Repair. CoRR (2017)
Ke Wang, Rishabh Singh, Zhendong Su
Data-Driven Feedback Generation for Introductory Programming Exercises. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rishabh Singh