Masa-aki Sato
Cognitive Neuroscience · 2000–2008
A researcher in the Science corpus: 8 papers; trusts 22 researchers and is trusted by 105 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 33 citations into it; #8,249 of 10,852 by trust here, #4,443 by citations
- Artificial Intelligence — 18 citations into it; #1,876 of 35,345 by trust here, #13,353 by citations
- Reinforcement Learning — 13 citations into it
- Probabilistic & Bayesian Methods — 12 citations into it; #138 of 1,525 by trust here, #648 by citations
- Computer Vision and Pattern Recognition — 9 citations into it
- Optimization & Training — 5 citations into it
- Statistics and Probability — 5 citations into it; #396 of 12,932 by trust here, #2,309 by citations
Whom Masa-aki Sato trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Shun-ichi Amari
- Radford M. Neal
- Michael I. Jordan
- Naonori Ueda
- Geoffrey E. Hinton
- Michael E. Tipping
- David John Cameron MacKay
- Robert A. Jacobs
- Lawrence R. Rabiner
- Zoubin Ghahramani
Who trusts Masa-aki Sato overall
- David M. Blei
- Antti Honkela
- Matthew D. Hoffman
- Thang D. Bui
- Yarin Gal
- Cuong V Nguyen
- Mohammad Emtiyaz Khan
- Matthew J. Beal
- Chong Wang
- Linda S. L. Tan
Papers from Masa-aki Sato's perspective
Ordered by how strongly the researchers Masa-aki Sato 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Reinforcement Learning: An Introduction
Their papers
- Online Model Selection Based on the Variational Bayes (2001) — 432 citations
- Reinforcement Learning for Biped Locomotion (2002) — 38 citations
- A Bayesian missing value estimation method for gene expression profile data (2003) — 790 citations
- Learning CPG-based biped locomotion with a policy gradient method (2005) — 32 citations
- Visual image reconstruction from human brain activity using a combination of multiscale local image decoders. (2008) — 603 citations
- Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns (2008) — 371 citations
- Hierarchical Bayesian estimation for MEG inverse problem (2004) — 292 citations
- On-line EM Algorithm for the Normalized Gaussian Network (2000) — 311 citations