Tejas Srinivasan

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 4 papers; trusts 325 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it
• Computer Vision and Pattern Recognition — 71 citations into it
• Natural Language Processing — 53 citations into it
• Multimodal Learning — 35 citations into it
• Evaluation & Benchmarks — 15 citations into it
• Model Architectures — 13 citations into it
• Large Language Models — 10 citations into it
• Optimization & Training — 6 citations into it

Whom Tejas Srinivasan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Shaoqing Ren
8. Ross B. Girshick
9. Yann LeCun
10. Oriol Vinyals

Who trusts Tejas Srinivasan overall

1. Baolin Peng
2. Zhaojiang Lin

Papers from Tejas Srinivasan's perspective

Ordered by how strongly the researchers Tejas Srinivasan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Structured Fusion Networks for Dialog (2019) — 94 citations
• CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks (2022) — 94 citations
• VAuLT: Augmenting the Vision-and-Language Transformer with the Propagation of Deep Language Representations (2022) — 12 citations
• Looking Enhances Listening: Recovering Missing Speech Using Images (2020) — 15 citations