Thomas Alexander Trost
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 3 papers; trusts 26 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 66 citations into it; #26,371 of 35,345 by trust here, #19,873 by citations
- Safety, Robustness & Interpretability — 39 citations into it
- Computer Vision and Pattern Recognition — 24 citations into it
- Optimization & Training — 11 citations into it
Whom Thomas Alexander Trost trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Yoshua Bengio
- Yann LeCun
- Kaiming He
- Geoffrey E. Hinton
- Christian Szegedy
- Ilya Sutskever
- L. Eon Bottou
- Diederik P. Kingma
- X. Zhang
Who trusts Thomas Alexander Trost overall
Papers from Thomas Alexander Trost's perspective
Ordered by how strongly the researchers Thomas Alexander Trost 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)
- 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
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Logit Pairing Methods Can Fool Gradient-Based Attacks (2018) — 87 citations
- On the security relevance of weights in deep learning. (2020)
- Adversarial Initialization - when your network performs the way I want (2019) — 8 citations