Miguel Pato

Nuclear and High Energy Physics · 2011–2019

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

Subfields

Whom Miguel Pato trusts overall

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

  1. G. Bertone

Who trusts Miguel Pato overall

  1. Christoph Weniger
  2. T. Bringmann
  3. S. Garbari
  4. T. Cohen

Papers from Miguel Pato's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Fully convolutional networks for semantic segmentation
  3. Do Deep Nets Really Need to be Deep?
  4. On the Convergence of Adam and Beyond
  5. Spectral–Spatial Feature Extraction for Hyperspectral Image Classification: A Dimension Reduction and Deep Learning Approach (IEEE Transactions on Geoscience and Remote Sensing)
  6. The Loss Surface of Multilayer Networks
  7. Deep learning in remote sensing: a review (arXiv.org)
  8. Convolutional Neural Networks for Large-Scale Remote-Sensing Image Classification (IEEE Transactions on Geoscience and Remote Sensing)
  9. Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing)
  10. Deep vs. shallow networks : An approximation theory perspective

Their papers