Panos Stinis
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 43 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 24 citations into it; #22,547 of 35,345 by trust here, #34,213 by citations
- Computer Vision and Pattern Recognition — 9 citations into it
- Model Architectures — 9 citations into it
- Reinforcement Learning — 9 citations into it
- Statistical and Nonlinear Physics — 8 citations into it
- Optimization & Training — 7 citations into it
Whom Panos Stinis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Christopher J. C. H. Watkins
- Ernst Hairer
- David Silver
- Richard S. Sutton
- Ivo Grondman
- Peter S. Dayan
- Timothy P. Lillicrap
- Volodymyr Mnih
- Geoffrey E. Hinton
- Yoshua Bengio
Who trusts Panos Stinis overall
Papers from Panos Stinis's perspective
Ordered by how strongly the researchers Panos Stinis 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)
- 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- GENERATIVE ADVERSARIAL NETS
Their papers
- Doing the Impossible: Why Neural Networks Can Be Trained at All (2018) — 21 citations
- Enforcing Constraints for Time Series Prediction in Supervised, Unsupervised and Reinforcement Learning (2019) — 14 citations