Rishabh Bhardwaj

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 173 citations into it; #21,933 of 35,345 by trust here, #26,682 by citations
• Natural Language Processing — 41 citations into it; #3,713 of 5,688 by trust here, #4,793 by citations
• Representation & Self-Supervised Learning — 22 citations into it
• Evaluation & Benchmarks — 14 citations into it
• Safety, Robustness & Interpretability — 11 citations into it; #1,431 of 2,251 by trust here, #2,014 by citations

Whom Rishabh Bhardwaj trusts overall

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

1. Saif M. Mohammad
2. Svetlana Kiritchenko
3. Geoffrey E. Hinton
4. Elena Voita
5. Yoshua Bengio
6. Diederik P. Kingma
7. Alex Graves
8. Ari S. Morcos
9. Alex Krizhevsky
10. Christine Basta

Who trusts Rishabh Bhardwaj overall

1. Karolina Stańczak
2. Yusuke Hirota
3. Xisen Jin
4. Isabelle Augenstein
5. Piotr Pikekos
6. Yuta Nakashima
7. Soujanya Poria
8. Francesco Barbieri
9. Alexandra Sasha Luccioni

Papers from Rishabh Bhardwaj's perspective

Ordered by how strongly the researchers Rishabh Bhardwaj 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. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Investigating Gender Bias in BERT (2020) — 125 citations
• A review of deep learning techniques for speech processing (2023) — 354 citations