Francesco Iorio
Molecular Biology · 2009–2018
A researcher in the Science corpus: 4 papers; trusts 33 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 52 citations into it
- Computational Theory and Mathematics — 22 citations into it
- Computer Vision and Pattern Recognition — 7 citations into it; #6,201 of 21,575 by trust here, #12,992 by citations
- Statistics and Probability — 6 citations into it
Whom Francesco Iorio trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Paolo Brandimarte
- Giovanni Russo
- Richard Socher
- Trevor J. Hastie
- Richard D. Gonzalez
- Chun Wei Yap
- Ross B. Girshick
- Saurabh Gupta
- J. Urgen Schmidhuber
- Yann LeCun
Who trusts Francesco Iorio overall
- Shuhao Cao
- Sangseung Lee
- Johannes Brandstetter
- Han Gao
- Nikola B. Kovachki
- Zong-Yi Li
- Ashish Kumar
- Sangeun Oh
- Byungsoo Kim
- Chris J. Oates
Papers from Francesco Iorio's perspective
Ordered by how strongly the researchers Francesco Iorio trusts endorse each paper. Same corpus, a different order for every researcher.
- Gradient-based learning applied to document recognition
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Convolutional Neural Networks for Steady Flow Approximation (2016) — 911 citations
- Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties (2012) — 475 citations
- Drug repurposing: progress, challenges and recommendations (2018) — 3,866 citations
- A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches. (2009) — 413 citations