Alban Desmaison
Artificial Intelligence · 2016–2023
A researcher in the Science corpus: 6 papers; trusts 25 researchers and is trusted by 72 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 71 citations into it; #22,129 of 35,345 by trust here, #548 by citations
- Computer Vision and Pattern Recognition — 58 citations into it
- Probabilistic & Bayesian Methods — 35 citations into it
- Generative Models — 34 citations into it
Whom Alban Desmaison trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ruslan Salakhutdinov
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Ronan Collobert
- Radford M. Neal
- Ilya Sutskever
- Alex Graves
Who trusts Alban Desmaison overall
- Sebastian Hofstätter
- Timo Schick
- Da-Wei Zhou
- Yoshua Bengio
- Ali Ayub
- Sewon Min
- Andrew Zisserman
- Zhe Gan
- Yi Yang
- Ruslan Salakhutdinov
Papers from Alban Desmaison's perspective
Ordered by how strongly the researchers Alban Desmaison 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Auto-Encoding Variational Bayes (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- PyTorch: An Imperative Style, High-Performance Deep Learning Library (2019) — 53,912 citations
- Learning Disentangled Representations with Semi-Supervised Deep Generative Models (2017) — 378 citations
- PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel (2023) — 795 citations
- Deep Generative Models (2022) — 53 citations
- Automatic differentiation in PyTorch (2017) — 16,222 citations
- Inducing Interpretable Representations with Variational Autoencoders (2016) — 7 citations