M. Kroiss

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 5 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom M. Kroiss trusts overall

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

  1. Richard S. Sutton
  2. J. Urgen Schmidhuber
  3. Ronald J. Williams
  4. Satinder Singh
  5. Geoffrey E. Hinton
  6. Andrew Barto
  7. Yoshua Bengio

Papers from M. Kroiss's perspective

Ordered by how strongly the researchers M. Kroiss 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. Attention is All you Need (Neural Information Processing Systems)
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Asynchronous Methods for Deep Reinforcement Learning
  8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  9. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers