Maxime Gazeau
Artificial Intelligence · 2019
A researcher in the Science corpus: 2 papers; trusts 42 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 79 citations into it
- Optimization & Training — 71 citations into it
- Computer Vision and Pattern Recognition — 43 citations into it
- Computational Mechanics — 26 citations into it
- Scaling & Learning Theory — 18 citations into it
- Statistical and Nonlinear Physics — 8 citations into it
Whom Maxime Gazeau trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- James Martens
- L. Eon Bottou
- Alex Krizhevsky
- Yann LeCun
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Kaiming He
- Karen Simonyan
- Diederik P. Kingma
Papers from Maxime Gazeau's perspective
Ordered by how strongly the researchers Maxime Gazeau 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)