Hiroshi Sasaki

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 208 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 30 citations into it
• Generative Models — 23 citations into it
• Artificial Intelligence — 14 citations into it
• Model Architectures — 7 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it
• Optimization & Training — 5 citations into it
• Signal Processing — 5 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Hiroshi Sasaki trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Diederik P. Kingma
4. Yoshua Bengio
5. Pascal Vincent
6. Alex Krizhevsky
7. Sergey Ioffe
8. Yann LeCun
9. Christian Szegedy
10. Ilya Sutskever

Who trusts Hiroshi Sasaki overall

1. Julia Wolleb
2. Sam Bond-Taylor
3. Alexia Jolicoeur-Martineau
4. Andreas Blattmann
5. Zhengxiong Luo
6. Fan Bao
7. Florentin Bieder
8. Tim Dockhorn
9. Adam Leach
10. Robin Sandkühler

Papers from Hiroshi Sasaki's perspective

Ordered by how strongly the researchers Hiroshi Sasaki trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models (2021) — 220 citations