Satish Chandra
Information Systems · 2007–2020
A researcher in the Science corpus: 10 papers; trusts 75 researchers and is trusted by 31 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 129 citations into it; #955 of 8,771 by trust here, #727 by citations
- Artificial Intelligence — 111 citations into it; #13,217 of 35,345 by trust here, #11,327 by citations
- Software — 79 citations into it; #215 of 1,227 by trust here, #158 by citations
- Natural Language Processing — 61 citations into it; #4,525 of 5,688 by trust here, #4,449 by citations
- Signal Processing — 41 citations into it
- Code Generation & Program Synthesis — 36 citations into it; #48 of 220 by trust here, #32 by citations
- Program Analysis & Verification — 36 citations into it; #153 of 301 by trust here, #51 by citations
- Computer Networks and Communications — 30 citations into it
Whom Satish Chandra trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Miltiadis Allamanis
- Claire Le Goues
- Yoshua Bengio
- Tomas Mikolov
- Sepp Hochreiter
- Geoffrey E. Hinton
- Ilya Sutskever
- Diederik P. Kingma
- Aseem Rastogi
- Oriol Vinyals
Who trusts Satish Chandra overall
- Erik Krogh Kristensen
- Claire Le Goues
- Michael Pradel
- Sergey Mechtaev
- Milod Kazerounian
- Anders Møller
- Qihao Zhu
- Baptiste Rozière
- Fan Long
- Rishabh Singh
Papers from Satish Chandra's perspective
Ordered by how strongly the researchers Satish Chandra trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
Their papers
- TypeWriter: neural type prediction with search-based validation (2019) — 135 citations
- Code Prediction by Feeding Trees to Transformers (2020) — 241 citations
- When deep learning met code search (2019) — 239 citations
- Scaffle: bug localization on millions of files (2020) — 40 citations
- Getafix: learning to fix bugs automatically (2019) — 271 citations
- Retrieval on source code: a neural code search (2018) — 200 citations
- Aroma: code recommendation via structural code search (2018) — 171 citations
- Type inference for static compilation of JavaScript (2016) — 42 citations
- SemFix: Program repair via semantic analysis (2013) — 776 citations
- A survey of static analysis methods for identifying security vulnerabilities in software systems (2007) — 100 citations