Léo Grinsztajn
Artificial Intelligence · 2022
A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 55 citations into it
- Computer Vision and Pattern Recognition — 24 citations into it
- ML Systems & Hardware — 6 citations into it
- Optimization & Training — 6 citations into it
Whom Léo Grinsztajn trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrew Y. Ng
- Tianqi Chen
- Yu. V. Gorishniy
- Carlos Guestrin
- Geoffrey E. Hinton
- Sergei Popov
- Joaquin Vanschoren
- Matthias Feurer
- Ivan Rubachev
- Xin Huang
Who trusts Léo Grinsztajn overall
Papers from Léo Grinsztajn's perspective
Ordered by how strongly the researchers Léo Grinsztajn 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)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Why do tree-based models still outperform deep learning on tabular data? (2022) — 618 citations
- Why do tree-based models still outperform deep learning on typical tabular data? (2022) — 1,782 citations