Maximilian Sölch

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #21,246 of 35,345 by trust here, #13,353 by citations
• Generative Models — 8 citations into it; #1,239 of 1,956 by trust here, #1,054 by citations
• Probabilistic & Bayesian Methods — 8 citations into it

Whom Maximilian Sölch trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Graves
4. Max Welling
5. Danilo Jimenez Rezende
6. L. Eon Bottou
7. Manuel Watter
8. Yoshua Bengio
9. Zoubin Ghahramani

Who trusts Maximilian Sölch overall

1. Danijar Hafner
2. Hao Wang
3. Joseph Marino
4. Naoya Takeishi
5. Daehyung Park
6. Timothy P. Lillicrap
7. Timothée Lesort
8. Marco Fraccaro
9. Jeremy Morton
10. Nan Rosemary Ke

Papers from Maximilian Sölch's perspective

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

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

Their papers

• Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data (2016) — 417 citations