Anand Ashok Sawant
Artificial Intelligence · 2021–2023
A researcher in the Science corpus: 2 papers; trusts 52 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 44 citations into it; #24,206 of 35,345 by trust here, #33,294 by citations
- Information Systems — 32 citations into it; #5,401 of 8,771 by trust here, #8,258 by citations
- Natural Language Processing — 29 citations into it
- Software — 17 citations into it
- Computer Vision and Pattern Recognition — 16 citations into it
- Program Analysis & Verification — 12 citations into it
- Code Generation & Program Synthesis — 11 citations into it; #129 of 220 by trust here, #214 by citations
- Signal Processing — 9 citations into it
Whom Anand Ashok Sawant trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Miltiadis Allamanis
- Vincent J. Hellendoorn
- Geoffrey E. Hinton
- Iasonas Kokkinos
- Premkumar T. Devanbu
- Yoshua Bengio
- Yann LeCun
- Diederik P. Kingma
- Earl T. Barr
- Ilya Sutskever
Who trusts Anand Ashok Sawant overall
Papers from Anand Ashok Sawant's perspective
Ordered by how strongly the researchers Anand Ashok Sawant trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- 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)
- 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
Their papers
- The growing cost of deep learning for source code (2021) — 21 citations
- Learning to Predict User-Defined Types (2023) — 13 citations