Sander M. Bohte

Artificial Intelligence · 2000–2021

A researcher in the Science corpus: 5 papers; trusts 143 researchers and is trusted by 35 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it; #9,899 of 35,345 by trust here, #15,236 by citations
• Model Architectures — 28 citations into it; #782 of 2,278 by trust here, #1,601 by citations
• Computer Vision and Pattern Recognition — 27 citations into it
• Electrical and Electronic Engineering — 19 citations into it; #2,498 of 16,539 by trust here, #7,770 by citations
• Signal Processing — 18 citations into it; #1,578 of 7,572 by trust here, #2,816 by citations
• Management Science and Operations Research — 16 citations into it; #2,194 of 11,946 by trust here, #3,705 by citations
• Cognitive Neuroscience — 14 citations into it; #2,292 of 10,852 by trust here, #4,716 by citations
• Optimization & Training — 13 citations into it

Whom Sander M. Bohte trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Yann LeCun
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. Sepp Hochreiter
7. Wolfgang Maass
8. Alex Krizhevsky
9. G. Zhang
10. Aäron van den Oord

Who trusts Sander M. Bohte overall

1. Filip Ponulak
2. Hesham Mostafa
3. J. Urgen Schmidhuber
4. Samanwoy Ghosh-Dastidar
5. Michael Pfeiffer
6. Andrzej J. Kasinski
7. Sumit Bam Shrestha
8. Xiang Gao
9. Amos Sironi
10. Hojjat Adeli

Papers from Sander M. Bohte's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Error-backpropagation in temporally encoded networks of spiking neurons (2000) — 1,033 citations
• Conditional Time Series Forecasting with Convolutional Neural Networks (2017) — 591 citations
• Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks (2021) — 321 citations
• Dilated convolutional neural networks for time series forecasting (2018) — 117 citations
• IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015) — 46 citations