Nur Muhammad (Mahi) Shafiullah

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 2 papers; trusts 134 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 72 citations into it; #20,183 of 35,345 by trust here, #13,544 by citations
• Computer Vision and Pattern Recognition — 36 citations into it
• Reinforcement Learning — 35 citations into it
• Safety, Robustness & Interpretability — 24 citations into it; #1,406 of 2,251 by trust here, #1,569 by citations
• Control and Systems Engineering — 12 citations into it; #5,027 of 8,257 by trust here, #2,692 by citations
• Evaluation & Benchmarks — 11 citations into it
• Natural Language Processing — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Nur Muhammad (Mahi) Shafiullah trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yoshua Bengio
6. Yann LeCun
7. Ross B. Girshick
8. Ilya Sutskever
9. Alex Graves
10. J. Urgen Schmidhuber

Who trusts Nur Muhammad (Mahi) Shafiullah overall

1. Eric Wong
2. Hongtao Wu
3. Tim Pearce

Papers from Nur Muhammad (Mahi) Shafiullah's perspective

Ordered by how strongly the researchers Nur Muhammad (Mahi) Shafiullah 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Behavior Transformers: Cloning k modes with one stone (2022) — 421 citations
• Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability (2018) — 211 citations