Markus Kunesch

Artificial Intelligence · 2015–2025

A researcher in the Science corpus: 4 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Markus Kunesch trusts

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

  1. A. P. Dawid (in Statistics and Probability)
  2. Tom L. Burr (in Artificial Intelligence)
  3. Paul J. Werbos (in Optimization & Training)
  4. Silvia Chiappa (in Safety, Robustness & Interpretability)

Papers from Markus Kunesch's perspective

Ordered by how strongly the researchers Markus Kunesch 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. Long Short-Term Memory
  3. Reinforcement Learning: An Introduction
  4. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. ImageNet classification with deep convolutional neural networks
  7. Gradient-based learning applied to document recognition
  8. IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Information Theory: 1948-1998 - Guest Editorial

Their papers