Jason Mars

Computer Vision and Pattern Recognition · 2011–2019

A researcher in the Science corpus: 6 papers; trusts 96 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 54 citations into it; #17,933 of 21,575 by trust here, #7,176 by citations
• Artificial Intelligence — 51 citations into it
• Hardware and Architecture — 29 citations into it; #1,469 of 1,551 by trust here, #954 by citations
• Computer Networks and Communications — 23 citations into it; #6,926 of 9,886 by trust here, #1,992 by citations
• Efficiency & Compression — 23 citations into it; #1,020 of 1,264 by trust here, #633 by citations
• Electrical and Electronic Engineering — 21 citations into it
• Natural Language Processing — 18 citations into it
• Aerospace Engineering — 10 citations into it

Whom Jason Mars trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Moinuddin K. Qureshi
5. Karen Simonyan
6. Kaiming He
7. Yoshua Bengio
8. Ilya Sutskever
9. Andrew Zisserman
10. Asit K. Mishra

Who trusts Jason Mars overall

1. David Lo
2. Liqun Cheng
3. Christina Delimitrou
4. Christos Kozyrakis
5. Rama K. Govindaraju
6. D. Narayanan

Papers from Jason Mars's perspective

Ordered by how strongly the researchers Jason Mars 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. Gradient-based learning applied to document recognition
4. Going deeper with convolutions
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet Large Scale Visual Recognition Challenge
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Gist: Efficient Data Encoding for Deep Neural Network Training (2018) — 155 citations
• An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction (2019) — 648 citations
• The Architectural Implications of Autonomous Driving: Constraints and Acceleration (2018) — 488 citations
• Data Collection for Dialogue System: A Startup Perspective (2018) — 32 citations
• Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge (2017) — 1,544 citations
• Bubble-up: Increasing utilization in modern warehouse scale computers via sensible co-locations (2011) — 649 citations