Md. Mostofa Ali Patwary

Artificial Intelligence · 2014–2017

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it; #18,704 of 35,345 by trust here, #3,673 by citations
• Computer Vision and Pattern Recognition — 30 citations into it
• Optimization & Training — 16 citations into it; #1,807 of 2,601 by trust here, #575 by citations
• Probabilistic & Bayesian Methods — 16 citations into it; #1,116 of 1,525 by trust here, #251 by citations
• Scaling & Learning Theory — 14 citations into it; #422 of 428 by trust here, #176 by citations
• Computational Theory and Mathematics — 12 citations into it; #7,308 of 12,182 by trust here, #641 by citations
• Evaluation & Benchmarks — 7 citations into it
• Statistical Learning Theory — 7 citations into it

Whom Md. Mostofa Ali Patwary trusts overall

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

1. Radford M. Neal
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yehuda Koren
5. Jasper Snoek
6. Shun-ichi Amari
7. Alex Krizhevsky
8. Diederik P. Kingma
9. Haewoon Kwak
10. Ilya Sutskever

Who trusts Md. Mostofa Ali Patwary overall

1. Tae Jun Ham

Papers from Md. Mostofa Ali Patwary's perspective

Ordered by how strongly the researchers Md. Mostofa Ali Patwary 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. ImageNet Large Scale Visual Recognition Challenge
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Microsoft COCO: Common Objects in Context

Their papers

• Deep Learning Scaling is Predictable, Empirically (2017) — 1,031 citations
• Scalable Bayesian Optimization Using Deep Neural Networks (2015) — 1,144 citations
• GraphMat: High performance graph analytics made productive (2015) — 344 citations
• Navigating the maze of graph analytics frameworks using massive graph datasets (2014) — 202 citations