Josh Fromm
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 2 papers; trusts 33 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 15 citations into it; #28,156 of 35,345 by trust here, #33,294 by citations
- Computer Vision and Pattern Recognition — 15 citations into it; #17,264 of 21,575 by trust here, #20,756 by citations
- Efficiency & Compression — 10 citations into it
- Radiology, Nuclear Medicine and Imaging — 8 citations into it
- Biomedical Engineering — 7 citations into it
- Cardiology and Cardiovascular Medicine — 5 citations into it
Whom Josh Fromm trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Matthieu Courbariaux
- Alex Krizhevsky
- Yoshua Bengio
- Geoffrey E. Hinton
- Song Han
- Ilya Sutskever
- Matthew D. Zeiler
- Wei-Yao Tang
- Yunchao Gong
- Yann LeCun
Who trusts Josh Fromm overall
Papers from Josh Fromm's perspective
Ordered by how strongly the researchers Josh Fromm trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (2020) — 405 citations
- Heterogeneous Bitwidth Binarization in Convolutional Neural Networks (2018) — 29 citations