Baishakhi Ray
Artificial Intelligence · 2013–2022
A researcher in the Science corpus: 16 papers; trusts 266 researchers and is trusted by 31 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 255 citations into it; #9,728 of 35,345 by trust here, #5,390 by citations
- Information Systems — 222 citations into it; #1,634 of 8,771 by trust here, #737 by citations
- Software — 146 citations into it; #222 of 1,227 by trust here, #93 by citations
- Natural Language Processing — 141 citations into it; #3,053 of 5,688 by trust here, #2,529 by citations
- Signal Processing — 80 citations into it; #2,771 of 7,572 by trust here, #945 by citations
- Computer Vision and Pattern Recognition — 76 citations into it; #12,348 of 21,575 by trust here, #9,079 by citations
- Safety, Robustness & Interpretability — 62 citations into it; #1,303 of 2,251 by trust here, #1,023 by citations
- Code Generation & Program Synthesis — 56 citations into it; #63 of 220 by trust here, #16 by citations
Whom Baishakhi Ray trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Premkumar T. Devanbu
- Miltiadis Allamanis
- Yoshua Bengio
- Geoffrey E. Hinton
- Diederik P. Kingma
- Veselin Raychev
- Ilya Sutskever
- Alex Krizhevsky
- David M. Blei
- Vladimir Naumovich Vapni
Who trusts Baishakhi Ray overall
- Vincent J. Hellendoorn
- Yi Li
- Rafael-Michael Karampatsis
- Saikat Chakraborty
- Yangruibo Ding
- Miltiadis Allamanis
- Zheng Gao
- Tien Nhut Nguyen
- Shaohua Wang
- Christian Bird
Papers from Baishakhi Ray's perspective
Ordered by how strongly the researchers Baishakhi Ray 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)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Unified Pre-training for Program Understanding and Generation (2021) — 938 citations
- A Transformer-based Approach for Source Code Summarization (2020) — 456 citations
- Building Language Models for Text with Named Entities (2018) — 46 citations
- Multi-lingual Evaluation of Code Generation Models (2022) — 247 citations
- DeepTest: Automated Testing of Deep-Neural-Network-Driven Autonomous Cars (2017) — 1,513 citations
- Metric Learning for Adversarial Robustness (2019) — 204 citations
- An Empirical Study of API Stability and Adoption in the Android Ecosystem (2013) — 315 citations
- ReCode: Robustness Evaluation of Code Generation Models (2022) — 161 citations
- Deep Learning Based Vulnerability Detection: Are We There Yet? (2020) — 789 citations
- Patching as Translation: the Data and the Metaphor (2020) — 77 citations
- CODIT: Code Editing With Tree-Based Neural Models (2018) — 131 citations
- Cross-project code clones in GitHub (2018) — 40 citations
- Gender and Tenure Diversity in GitHub Teams (2015) — 394 citations
- On the "Naturalness" of Buggy Code (2015) — 299 citations
- Using Frankencerts for Automated Adversarial Testing of Certificate Validation in SSL/TLS Implementations (2014) — 248 citations
- A large scale study of programming languages and code quality in github (2014) — 440 citations