Christian Gumbsch

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 30 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Model Architectures — 13 citations into it
• Reinforcement Learning — 10 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Christian Gumbsch trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Yoshua Bengio
3. Ronald J. Williams
4. Richard S. Sutton
5. J. Urgen Schmidhuber
6. Andrew Barto
7. Geoffrey E. Hinton
8. Sepp Hochreiter
9. Jeffrey L. Elman
10. Alex Graves

Who trusts Christian Gumbsch overall

1. Maxime Chevalier-Boisvert

Papers from Christian Gumbsch's perspective

Ordered by how strongly the researchers Christian Gumbsch trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains (2021) — 28 citations