Satwik Bhattamishra
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 32 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 50 citations into it; #7,772 of 35,345 by trust here, #8,283 by citations
- Natural Language Processing — 45 citations into it; #1,651 of 5,688 by trust here, #1,874 by citations
- Computer Vision and Pattern Recognition — 13 citations into it; #19,100 of 21,575 by trust here, #15,955 by citations
- Evaluation & Benchmarks — 10 citations into it
- Information Systems — 7 citations into it; #1,274 of 8,771 by trust here, #1,265 by citations
- Model Architectures — 6 citations into it
Whom Satwik Bhattamishra trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Yoshua Bengio
- Geoffrey E. Hinton
- Sepp Hochreiter
- Ilya Sutskever
- Thang Luong
- Dzmitry Bahdanau
- Alex Krizhevsky
- Christopher D. Manning
- Jimmy Ba
Who trusts Satwik Bhattamishra overall
- Wenhu Chen
- Pan Lu
- Yifei Li
- Jason Wei
- Lei Wang
- Jianing Zhou
- Yihuai Lan
- Geunwoo Kim
- Jiaao Chen
- Namgyu Ho
Papers from Satwik Bhattamishra's perspective
Ordered by how strongly the researchers Satwik Bhattamishra trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- ImageNet classification with deep convolutional neural networks
- 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Are NLP Models really able to Solve Simple Math Word Problems? (2021) — 1,284 citations
- Submodular Optimization-based Diverse Paraphrasing and its Effectiveness in Data Augmentation (2019) — 128 citations