Ricard Marxer

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 6 papers; trusts 38 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

Whom Ricard Marxer trusts overall

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

  1. Marina Meila
  2. Geoffrey E. Hinton
  3. Matthew J. Johnson
  4. Douglas Eck
  5. Martin Mächler
  6. Silke Wagner
  7. J. Urgen Schmidhuber
  8. David H. Ackley
  9. Ying Zhao
  10. Emily B. Fox

Who trusts Ricard Marxer overall

  1. Mirco Ravanelli
  2. Jan Chorowski
  3. Shinji Watanabe
  4. Zhong Meng
  5. Yoshua Bengio
  6. Ron J. Weiss
  7. Philemon Brakel
  8. Jinyu Li
  9. Maurizio Omologo
  10. Wei-Ning Hsu

Papers from Ricard Marxer's perspective

Ordered by how strongly the researchers Ricard Marxer 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. Long Short-Term Memory
  3. ImageNet classification with deep convolutional neural networks
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers