Shubhra (Santu) Karmaker

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 57 citations into it
• Natural Language Processing — 25 citations into it
• Evaluation & Benchmarks — 22 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Large Language Models — 5 citations into it

Whom Shubhra (Santu) Karmaker trusts overall

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

1. Yoshua Bengio
2. Randal S. Olson
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Ilya Sutskever
7. Frank Hutter
8. Chin-Yew Lin
9. Yann LeCun
10. Kaiming He

Who trusts Shubhra (Santu) Karmaker overall

1. Pengcheng Yin

Papers from Shubhra (Santu) Karmaker's perspective

Ordered by how strongly the researchers Shubhra (Santu) Karmaker trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• AutoML to Date and Beyond: Challenges and Opportunities (2020) — 326 citations
• Revisiting Automatic Evaluation of Extractive Summarization Task: Can We Do Better than ROUGE? (2022) — 50 citations