Michael Hahsler

Artificial Intelligence · 2006–2019

A researcher in the Science corpus: 9 papers; trusts 65 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Hahsler trusts overall

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

  1. Charu C. Aggarwal
  2. Martin Ester
  3. Rakesh Agrawal
  4. Dirk Eddelbuettel
  5. Yixin Chen
  6. Anil K. Jain
  7. David Ruppert
  8. Hans-Peter Kriegel
  9. Teuvo Kohonen
  10. Feng Cao

Who trusts Michael Hahsler overall

  1. Sebastian Schmidl
  2. Tyler L. Hayes
  3. Zuguang Gu
  4. Jiaming Zeng
  5. Zhenhua Zhang
  6. Ming Jin
  7. Matthew Bolaños
  8. Phillip Wenig
  9. Houtao Deng
  10. John Forrest

Papers from Michael Hahsler's perspective

Ordered by how strongly the researchers Michael Hahsler 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. ImageNet classification with deep convolutional neural networks
  3. Long Short-Term Memory
  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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers