James R. Clough

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 17 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it
• Artificial Intelligence — 19 citations into it; #23,787 of 35,345 by trust here, #24,417 by citations
• Representation & Self-Supervised Learning — 10 citations into it
• Natural Language Processing — 8 citations into it
• Computational Theory and Mathematics — 7 citations into it

Whom James R. Clough trusts overall

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

1. Diederik P. Kingma
2. Andriy Mnih
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Ilya Sutskever
6. Philipp Krahenbuhl
7. Andrew Zisserman
8. Yoshua Bengio
9. Yann LeCun
10. Alex Krizhevsky

Who trusts James R. Clough overall

1. William L. Hamilton
2. Ines Chami
3. Frederic Sala

Papers from James R. Clough's perspective

Ordered by how strongly the researchers James R. Clough 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Neural Embeddings of Graphs in Hyperbolic Space (2017) — 188 citations
• Global and Local Interpretability for Cardiac MRI Classification (2019) — 70 citations
• A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology (2019) — 309 citations