Sahil Bhatia
Information Systems · 2016–2018
A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 25 citations into it; #1,211 of 8,771 by trust here, #3,876 by citations
- Software — 19 citations into it; #154 of 1,227 by trust here, #456 by citations
- Code Generation & Program Synthesis — 16 citations into it
- Artificial Intelligence — 14 citations into it
- Natural Language Processing — 14 citations into it; #1,757 of 5,688 by trust here, #4,449 by citations
- Computer Science Applications — 8 citations into it; #211 of 1,855 by trust here, #1,093 by citations
- Model Architectures — 8 citations into it
- Program Analysis & Verification — 8 citations into it
Whom Sahil Bhatia trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Miltiadis Allamanis
- Premkumar T. Devanbu
- Charles Sutton
- David E. Rumelhart
- Armando Solar-Lezama
- Veselin Raychev
- Paul J. Werbos
- Rishabh Singh
- Earl T. Barr
- Geoffrey E. Hinton
Who trusts Sahil Bhatia overall
- Michael Pradel
- Rahul Gupta
- Miltiadis Allamanis
- Koushik Sen
- Yi Li
- Jacob Devlin
- Ke Wang
- Michele Tufano
- Rishabh Singh
- Aditya Kanade
Papers from Sahil Bhatia's perspective
Ordered by how strongly the researchers Sahil Bhatia trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Neuro-Symbolic Program Corrector for Introductory Programming Assignments (2018) — 96 citations
- Automated Correction for Syntax Errors in Programming Assignments using Recurrent Neural Networks (2016) — 120 citations