Paras Jain
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 5 papers; trusts 194 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 116 citations into it
- Computer Vision and Pattern Recognition — 91 citations into it
- Natural Language Processing — 34 citations into it
- Model Architectures — 31 citations into it
- Efficiency & Compression — 27 citations into it
- Information Systems — 27 citations into it
- Optimization & Training — 22 citations into it
- Representation & Self-Supervised Learning — 22 citations into it
Whom Paras Jain trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Karen Simonyan
- Ilya Sutskever
- Yann LeCun
- Ross B. Girshick
- Andrew Zisserman
Who trusts Paras Jain overall
- Yichen Xu
- Hieu Pham
- Phúc H. Lê Khắc
- Baptiste Rozière
- Zhuohan Li
- Ajay Jain
- Ji Lin
- Jiarui Fang
- Guanhua Wang
- Yanqiao Zhu
Papers from Paras Jain's perspective
Ordered by how strongly the researchers Paras Jain trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization (2019) — 244 citations
- POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging (2022) — 54 citations
- Representing Long-Range Context for Graph Neural Networks with Global Attention (2022) — 423 citations
- Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging (2022)
- Contrastive Code Representation Learning (2020) — 179 citations