Philipp Seeböck

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

Whom Philipp Seeböck trusts overall

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

  1. Diederik P. Kingma
  2. Alec Radford
  3. Geoffrey E. Hinton
  4. Tim Salimans
  5. Jimmy Ba
  6. Yoshua Bengio
  7. Deepak Pathak
  8. Alex Krizhevsky
  9. Sarah Monazam Erfani
  10. Raymond A. Yeh

Who trusts Philipp Seeböck overall

  1. Paul Bergmann
  2. Kilian Batzner
  3. Vitjan Zavrtanik
  4. Lukas Ruff
  5. Guansong Pang
  6. Denis A. Gudovskiy
  7. Jakob Bozic
  8. Christoph Baur
  9. Guodong Wang
  10. Julian Wyatt

Papers from Philipp Seeböck's perspective

Ordered by how strongly the researchers Philipp Seeböck 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. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Their papers