Thomas Pasquier

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Pasquier trusts overall

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

  1. Sadegh M. Milajerdi
  2. Moses Charikar
  3. Carl Doersch
  4. Peter J. Rousseeuw
  5. Ingo Steinwart
  6. Samuel T. King
  7. Ashish Gehani
  8. Leman Akoglu
  9. Olivier Chapelle
  10. Sariel Har-Peled

Papers from Thomas Pasquier's perspective

Ordered by how strongly the researchers Thomas Pasquier 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  7. Learning Multiple Layers of Features from Tiny Images
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers