Martin Schiegg
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 3 papers; trusts 68 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 58 citations into it
- Computer Vision and Pattern Recognition — 43 citations into it
- Representation & Self-Supervised Learning — 23 citations into it
- Probabilistic & Bayesian Methods — 9 citations into it
- Graph Learning — 5 citations into it
- Natural Language Processing — 5 citations into it
Whom Martin Schiegg trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Sepp Hochreiter
- Yann LeCun
- Kaiming He
- Ruslan Salakhutdinov
- Max Welling
Who trusts Martin Schiegg overall
Papers from Martin Schiegg's perspective
Ordered by how strongly the researchers Martin Schiegg 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Relational Generalized Few-Shot Learning (2019) — 27 citations
- ilastik: interactive machine learning for (bio)image analysis (2019) — 2,939 citations
- Probabilistic Recurrent State-Space Models (2018) — 149 citations