Jérôme Tubiana
Molecular Biology · 2018–2021
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
- Molecular Biology — 67 citations into it
- Computational Biology & Bioinformatics — 32 citations into it
- Artificial Intelligence — 20 citations into it
- Materials Chemistry — 16 citations into it
- Computer Vision and Pattern Recognition — 13 citations into it
- Genetics — 8 citations into it
- Model Architectures — 7 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
Whom Jérôme Tubiana trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Sergey Ioffe
- Ruslan Salakhutdinov
- B. Reva
- W. Kühlbrandt
- Simona Cocco
- Yoshua Bengio
- Vinod Nair
- Individualized Treat
- Christian Szegedy
Who trusts Jérôme Tubiana overall
Papers from Jérôme Tubiana's perspective
Ordered by how strongly the researchers Jérôme Tubiana 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)
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- ImageNet: A large-scale hierarchical image database
- GENERATIVE ADVERSARIAL NETS
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Learning protein constitutive motifs from sequence data (2018) — 115 citations
- ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction (2021) — 245 citations