Alois C. Knoll

Artificial Intelligence · 2006–2024

A researcher in the Science corpus: 9 papers; trusts 272 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 164 citations into it; #14,738 of 35,345 by trust here, #18,186 by citations
• Reinforcement Learning — 101 citations into it; #2,079 of 2,242 by trust here, #1,663 by citations
• Computer Vision and Pattern Recognition — 100 citations into it; #9,504 of 21,575 by trust here, #11,721 by citations
• Control and Systems Engineering — 52 citations into it
• Management Science and Operations Research — 39 citations into it
• Computational Theory and Mathematics — 29 citations into it
• Cognitive Neuroscience — 25 citations into it
• Optimization & Training — 21 citations into it

Whom Alois C. Knoll trusts overall

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

1. Robert E. Schapire
2. Jerome H. Friedman
3. Yoav Freund
4. Geoffrey E. Hinton
5. Xin Yao
6. Niko Speybroeck
7. Yifan Hu
8. Tong Zhang
9. C. Sutton
10. Radford M. Neal

Who trusts Alois C. Knoll overall

1. Ibomoiye Domor Mienye
2. Alexander Rakhlin
3. Azal Ahmad Khan
4. Y. Raita
5. J. Urgen Schmidhuber
6. Yanxia Sun

Papers from Alois C. Knoll's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. GENERATIVE ADVERSARIAL NETS
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks (2006) — 241 citations
• A Review of Safe Reinforcement Learning: Methods, Theories, and Applications (2024) — 298 citations
• A Survey of the Four Pillars for Small Object Detection: Multiscale Representation, Contextual Information, Super-Resolution, and Region Proposal (2022) — 306 citations
• A Review of Safe Reinforcement Learning: Methods, Theory and Applications (2022) — 328 citations
• Action recognition using ensemble weighted multi-instance learning (2014) — 23 citations
• Spatiotemporal Movement Planning and Rapid Adaptation for Manual Interaction (2013) — 18 citations
• Gradient boosting machines, a tutorial (2013) — 3,482 citations
• A sensor fusion approach for localization with cumulative error elimination (2012) — 43 citations
• Complex Valued Artificial Recurrent Neural Network as a Novel Approach to Model the Perceptual Binding Problem (2012) — 4 citations