Bastian Steudel

Artificial Intelligence · 2009–2012

A researcher in the Science corpus: 4 papers; trusts 18 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it; #6,437 of 35,345 by trust here, #7,310 by citations
• Causal Inference & Discovery — 21 citations into it; #104 of 364 by trust here, #60 by citations
• Information Theory — 12 citations into it; #100 of 196 by trust here, #40 by citations
• Computational Theory and Mathematics — 10 citations into it; #2,386 of 12,182 by trust here, #1,700 by citations
• Signal Processing — 9 citations into it; #3,201 of 7,572 by trust here, #2,052 by citations
• Probabilistic & Bayesian Methods — 8 citations into it
• Control and Systems Engineering — 6 citations into it
• Molecular Biology — 6 citations into it; #16,693 of 17,773 by trust here, #16,527 by citations

Whom Bastian Steudel trusts overall

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

1. Dominik Janzing
2. Joris M. Mooij
3. Peter Spirtes
4. Kun Zhang
5. Bernhard Schölkopf
6. Thomas Verma
7. Gregory J. Chaitin
8. Patrik O. Hoyer
9. Clark Glymour
10. Xiaoqi Zheng

Who trusts Bastian Steudel overall

1. Bernhard Schölkopf
2. Kailash Budhathoki
3. Dominik Janzing
4. Jan Peters
5. Jilles Vreeken
6. David Lopez-Paz
7. Joris M. Mooij
8. Kun Zhang
9. Francesco Locatello

Papers from Bastian Steudel's perspective

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

1. Information Theory: 1948-1998 - Guest Editorial
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. GENERATIVE ADVERSARIAL NETS
5. Learning Multiple Layers of Features from Tiny Images
6. Causation
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Gradient-based learning applied to document recognition
9. Nonlinear causal discovery with additive noise models
10. Long Short-Term Memory

Their papers

• Inferring deterministic causal relations (2010) — 202 citations
• Information-geometric approach to inferring causal directions (2012) — 317 citations
• Causal Markov condition for submodular information measures (2010) — 36 citations
• Justifying Additive Noise Model-Based Causal Discovery via Algorithmic Information Theory (2009) — 35 citations