Timon Schroeter
Artificial Intelligence · 2007–2011
A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 14 citations into it; #7,534 of 35,345 by trust here, #4,656 by citations
- Statistical Learning Theory — 10 citations into it
- Statistics and Probability — 6 citations into it
Whom Timon Schroeter trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Bernhard Schölkopf
- David Ruppert
- K. Müller
- Isabelle M Guyon
- Vladimir Naumovich Vapnik
- Alex Smola
- Vladimir Naumovich Vapni
- Masashi Sugiyama
- Eric R. Ziegel
- Carl E. Rasmussen
Who trusts Timon Schroeter overall
- Wojciech Samek
- Grgoire Montavon
- Been Kim
- Mukund Sundararajan
- K. Müller
- Sebastian Lapuschkin
- Pieter-Jan Kindermans
- Marco Tulio Ribeiro
- Ankur Taly
- Alexander Binder
Papers from Timon Schroeter's perspective
Ordered by how strongly the researchers Timon Schroeter 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- How to Explain Individual Classification Decisions (2009) — 1,191 citations
- Visual Interpretation of Kernel‐Based Prediction Models (2011) — 58 citations
- Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules (2007) — 59 citations
- Benchmark Data Set for in Silico Prediction of Ames Mutagenicity (2009) — 352 citations