L. Deiss

2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom L. Deiss trusts overall

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

1. Alex Smola
2. Muhammed Khlosi
3. Bernhard Schölkopf
4. Vladimir Naumovich Vapni
5. Peter Filzmoser

Who trusts L. Deiss overall

1. Abhinav Sharma
2. Arpit Jain

Papers from L. Deiss's perspective

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

1. The Nature of Statistical Learning Theory
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Learning Multiple Layers of Features from Tiny Images
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Going deeper with convolutions
10. ImageNet: A large-scale hierarchical image database

Their papers

• Tuning support vector machines regression models improves prediction accuracy of soil properties in MIR spectroscopy (2020) — 120 citations