Girish Sastry
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 8 papers; trusts 176 researchers and is trusted by 704 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 460 citations into it; #1,720 of 35,345 by trust here, #72 by citations
- Computer Vision and Pattern Recognition — 260 citations into it; #1,716 of 21,575 by trust here, #495 by citations
- Natural Language Processing — 211 citations into it
- Representation & Self-Supervised Learning — 108 citations into it; #1,217 of 3,145 by trust here, #57 by citations
- Reinforcement Learning — 30 citations into it; #1,942 of 2,242 by trust here, #1,545 by citations
Whom Girish Sastry trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Kaiming He
- Ilya Sutskever
- Yann LeCun
- Alex Graves
- Richard S. Sutton
- Christian Szegedy
Who trusts Girish Sastry overall
Papers from Girish Sastry's perspective
Ordered by how strongly the researchers Girish Sastry 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Learning Transferable Visual Models From Natural Language Supervision (2021) — 52,559 citations
- Language Models are Few-Shot Learners (2020) — 61,005 citations
- Evaluating Large Language Models Trained on Code (2021) — 10,663 citations
- Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations (2023) — 338 citations
- Trial without Error: Towards Safe Reinforcement Learning via Human Intervention (2017) — 277 citations
- Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims (2020) — 480 citations
- Text and Code Embeddings by Contrastive Pre-Training (2022) — 613 citations
- GPT-4 Technical Report (2023) — 26,133 citations