Neel Sundaresan
Artificial Intelligence · 2009–2023
A researcher in the Science corpus: 20 papers; trusts 341 researchers and is trusted by 37 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 206 citations into it; #8,135 of 35,345 by trust here, #5,221 by citations
- Natural Language Processing — 158 citations into it; #3,839 of 5,688 by trust here, #924 by citations
- Information Systems — 157 citations into it; #980 of 8,771 by trust here, #163 by citations
- Software — 101 citations into it; #160 of 1,227 by trust here, #10 by citations
- Computer Vision and Pattern Recognition — 91 citations into it; #12,687 of 21,575 by trust here, #8,296 by citations
- Large Language Models — 66 citations into it
- Code Generation & Program Synthesis — 64 citations into it
- Evaluation & Benchmarks — 50 citations into it
Whom Neel Sundaresan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Graves
- Ilya Sutskever
- Diederik P. Kingma
- Alex Krizhevsky
- Yann LeCun
- Kaiming He
- Ashish Vaswani
- Jimmy Ba
Who trusts Neel Sundaresan overall
- Daya Guo
- Yue Wang
- Julian McAuley
- Xinyun Chen
- Alexey Svyatkovskiy
- Shubham Chandel
- Colin B. Clement
- Maliheh Izadi
- Ruining He
- Hung Le
Papers from Neel Sundaresan's perspective
Ordered by how strongly the researchers Neel Sundaresan trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- PyMT5: Multi-mode Translation of Natural Language and Python Code with Transformers (2020) — 168 citations
- Large-Scale Video Summarization Using Web-Image Priors (2013) — 308 citations
- IntelliCode compose: code generation using transformer (2020) — 626 citations
- GraphCodeBERT: Pre-training Code Representations with Data Flow (2020) — 1,778 citations
- Large scale visual recommendations from street fashion images (2014) — 143 citations
- Training and Evaluating a Jupyter Notebook Data Science Assistant (2022) — 56 citations
- Rated aspect summarization of short comments (2009) — 414 citations
- Assessing Sale Strategies in Online Markets Using Matched Listings (2015) — 121 citations
- Sales Taxes and Internet Commerce (2014) — 178 citations
- Is a picture really worth a thousand words?: - on the role of images in e-commerce (2014) — 66 citations
- InferFix: End-to-End Program Repair with LLMs (2023) — 324 citations
- Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation (2023) — 51 citations
- METHODS2TEST: A dataset of focal methods mapped to test cases (2022) — 45 citations
- Generating bug-fixes using pretrained transformers (2021) — 60 citations
- CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation (2021) — 1,545 citations
- Unit Test Case Generation with Transformers (2020) — 292 citations
- Pythia: AI-assisted Code Completion System (2019) — 181 citations
- Auctions versus Posted Prices in Online Markets (2018) — 153 citations
- Style Finder: Fine-Grained Clothing Style Detection and Retrieval (2013)
- Palette power: enabling visual search through colors (2013) — 20 citations