Alexander Marx

Causal Inference & Discovery · 2017

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Causal Inference & Discovery — 8 citations into it
• Artificial Intelligence — 7 citations into it; #23,550 of 35,345 by trust here, #31,361 by citations
• Probabilistic & Bayesian Methods — 6 citations into it
• Computational Theory and Mathematics — 5 citations into it; #8,000 of 12,182 by trust here, #9,804 by citations

Whom Alexander Marx trusts overall

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

1. Dominik Janzing
2. Jorma Rissanen
3. Jan Peters
4. Joris M. Mooij
5. Thomas Verma
6. Yoav Benjamini
7. Chris S. Wallace
8. Kailash Budhathoki
9. Shohei Shimizu
10. Bernhard Schölkopf

Who trusts Alexander Marx overall

1. Niki Kilbertus
2. Diviyan Kalainathan
3. Giambattista Parascandolo
4. Bernhard Schölkopf
5. Olivier Goudet
6. Dominik Janzing

Papers from Alexander Marx's perspective

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

1. Causation, Prediction, and Search
2. ImageNet classification with deep convolutional neural networks
3. On the Identifiability of the Post-Nonlinear Causal Model
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. A Linear Non-Gaussian Acyclic Model for Causal Discovery
6. GENERATIVE ADVERSARIAL NETS
7. Learning Multiple Layers of Features from Tiny Images
8. Causality : Models , Reasoning , and Inference
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. Gradient-based learning applied to document recognition

Their papers

• Telling Cause from Effect Using MDL-Based Local and Global Regression (2017) — 71 citations