Maximilian Soelch

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Generative Models — 8 citations into it

Whom Maximilian Soelch trusts overall

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

1. Danilo Jimenez Rezende
2. J. Urgen Schmidhuber
3. Shakir Mohamed
4. Geoffrey E. Hinton
5. Maximilian Karl
6. Richard S. Sutton
7. Ruslan Salakhutdinov
8. Diederik P. Kingma

Papers from Maximilian Soelch's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. Stochastic Backpropagation and Approximate Inference in Deep Generative Models
9. ImageNet: A large-scale hierarchical image database
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Unsupervised Real-Time Control Through Variational Empowerment (2017) — 60 citations
• Navigation and planning in latent maps (2018)