François Soumis
Artificial Intelligence · 1993–2021
A researcher in the Science corpus: 9 papers; trusts 129 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 43 citations into it
- Computer Vision and Pattern Recognition — 17 citations into it
- Optimization & Training — 17 citations into it; #2,319 of 2,601 by trust here, #1,986 by citations
- Model Architectures — 14 citations into it
- Industrial and Manufacturing Engineering — 12 citations into it; #496 of 2,521 by trust here, #1,009 by citations
- Computer Networks and Communications — 8 citations into it; #9,132 of 9,886 by trust here, #8,844 by citations
- Natural Language Processing — 8 citations into it
- Management Science and Operations Research — 7 citations into it; #5,888 of 11,946 by trust here, #8,062 by citations
Whom François Soumis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Guy Desaulniers
- Alex Krizhevsky
- Sergey Ioffe
- Nitish Srivastava
- Ilya Sutskever
- Oriol Vinyals
- Diederik P. Kingma
- Christian Szegedy
Who trusts François Soumis overall
Papers from François Soumis's perspective
Ordered by how strongly the researchers François Soumis 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
- 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)
Their papers
- Airline crew scheduling: models, algorithms, and data sets (2014) — 137 citations
- Dynamic Constraint Aggregation for Solving Very Large-scale Airline Crew Pairing Problems (2020) — 12 citations
- Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer (2019) — 10 citations
- Machine Learning in Airline Crew Pairing to Construct Initial Clusters for Dynamic Constraint Aggregation (2020) — 26 citations
- Structured Convolutional Kernel Networks for Airline Crew Scheduling (2021) — 10 citations
- Multi-phase dynamic constraint aggregation for set partitioning type problems (2010) — 59 citations
- An extended branch-and-bound method for locomotive assignment (2003) — 59 citations
- Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling (2000) — 346 citations
- Crew Pairing at Air France (1993)