Bas H. M. van der Velden

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 2 papers; trusts 43 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it
• Computer Vision and Pattern Recognition — 45 citations into it
• Safety, Robustness & Interpretability — 18 citations into it
• Natural Language Processing — 10 citations into it
• Health Informatics — 7 citations into it
• Model Architectures — 7 citations into it
• Evaluation & Benchmarks — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Bas H. M. van der Velden trusts overall

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

1. Robert Tibshirani
2. Cynthia Rudin
3. Chin-Yew Lin
4. Sepp Hochreiter
5. Geoffrey E. Hinton
6. Lloyd S. Shapley
7. Diederik P. Kingma
8. Karen Simonyan
9. Alex Krizhevsky
10. Yoshua Bengio

Papers from Bas H. M. van der Velden's perspective

Ordered by how strongly the researchers Bas H. M. van der Velden 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Explainable artificial intelligence (XAI) in deep learning-based medical image analysis (2021) — 1,073 citations
• Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities (2016) — 339 citations