André Seyfarth
Biomedical Engineering · 2003–2015
A researcher in the Science corpus: 6 papers; trusts 33 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Biomedical Engineering — 21 citations into it; #2,383 of 10,734 by trust here, #4,866 by citations
- Artificial Intelligence — 18 citations into it; #23,881 of 35,345 by trust here, #19,873 by citations
- Reinforcement Learning — 11 citations into it
- Computational Theory and Mathematics — 10 citations into it; #9,335 of 12,182 by trust here, #5,239 by citations
- Control and Systems Engineering — 10 citations into it
- Mathematical Optimization — 9 citations into it
- Optimization & Training — 8 citations into it
- Management Science and Operations Research — 6 citations into it
Whom André Seyfarth trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Donald R. Jones
- Harold J. Kushner
- Roman Garnett
- Dimitri P. Bertsekas
- Hartmut Geyer
- Radford M. Neal
- Daniel J. Lizotte
- Richard R. Neptune
- Eric Brochu
- Felix E. Zajac
Who trusts André Seyfarth overall
- J. Rummel
- Pierre-Yves Oudeyer
- Hartmut Geyer
- Konstantinos Chatzilygeroudis
- Péter Englert
- Marvin Zhang
- Hugh M. Herr
- Rika Antonova
Papers from André Seyfarth's perspective
Ordered by how strongly the researchers André Seyfarth trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Reinforcement Learning: An Introduction
- Practical Bayesian Optimization of Machine Learning Algorithms
Their papers
- Bayesian optimization for learning gaits under uncertainty (2015) — 352 citations
- Toward fast policy search for learning legged locomotion (2012) — 38 citations
- Swing-leg retraction: a simple control model for stable running (2003) — 429 citations
- Compliant leg behaviour explains basic dynamics of walking and running (2006) — 1,013 citations
- An Experimental Evaluation of Bayesian Optimization on Bipedal Locomotion (2014) — 8 citations
- Manuscript: Stable Running with Segmented Legs ¤ (2008) — 156 citations