Ryutaro Tanno
Artificial Intelligence · 2018–2025
A researcher in the Science corpus: 6 papers; trusts 205 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 148 citations into it; #32,355 of 35,345 by trust here, #21,316 by citations
- Computer Vision and Pattern Recognition — 103 citations into it
- Model Architectures — 37 citations into it; #2,029 of 2,278 by trust here, #1,855 by citations
- Representation & Self-Supervised Learning — 15 citations into it
- Optimization & Training — 14 citations into it
- Safety, Robustness & Interpretability — 7 citations into it
- Probabilistic & Bayesian Methods — 6 citations into it
Whom Ryutaro Tanno trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Christian Szegedy
- Ilya Sutskever
- Karen Simonyan
- Alex Graves
Who trusts Ryutaro Tanno overall
- Emir Demirovi'c
- Vinícius G. Costa
- Sercan Ö. Arik
- Aaron M. Roth
- Simon Vandenhende
- Ruyi Ji
- Stephan Alaniz
- Peter James Stuckey
- Carlos Eduardo Pedreira
- Tomas Pfister
Papers from Ryutaro Tanno's perspective
Ordered by how strongly the researchers Ryutaro Tanno trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- Accelerating scientific discovery with Co-Scientist (2025) — 360 citations
- Towards conversational diagnostic artificial intelligence (2025) — 310 citations
- Capabilities of Gemini Models in Medicine (2024) — 407 citations
- Towards Generalist Biomedical AI (2023) — 549 citations
- Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels (2019) — 97 citations
- Adaptive Neural Trees (2018) — 181 citations