G. Sperl
Artificial Intelligence · 2016
A researcher in the Science corpus: 1 paper; trusts 59 researchers and is trusted by 338 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 30 citations into it; #952 of 35,345 by trust here, #1,101 by citations
- Computer Vision and Pattern Recognition — 26 citations into it
- Optimization & Training — 10 citations into it
- Meta & Continual Learning — 9 citations into it; #4 of 1,041 by trust here, #3 by citations
- Representation & Self-Supervised Learning — 8 citations into it; #127 of 3,145 by trust here, #134 by citations
Whom G. Sperl trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Kaiming He
- Ilya Sutskever
- Jimmy Ba
- Ruslan Salakhutdinov
- Nitish Srivastava
Who trusts G. Sperl overall
- Rahaf Aljundi
- Ali Ayub
- Da-Wei Zhou
- Tyler L. Hayes
- Gyuhak Kim
- Timothée Lesort
- Marc Masana
- Xialei Liu
- Yaoyao Liu
- Vincenzo Lomonaco
Papers from G. Sperl's perspective
Ordered by how strongly the researchers G. Sperl 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
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- iCaRL: Incremental Classifier and Representation Learning (2016) — 4,930 citations