Dagmar M. Schuller

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Dagmar M. Schuller trusts overall

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

  1. Alex Graves
  2. Diederik P. Kingma
  3. Geoffrey E. Hinton
  4. Karen Simonyan

Papers from Dagmar M. Schuller's perspective

Ordered by how strongly the researchers Dagmar M. Schuller 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Rectified Linear Units Improve Restricted Boltzmann Machines
  5. ImageNet classification with deep convolutional neural networks
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. This PDF file includes: Materials and Methods
  8. WaveNet: A Generative Model for Raw Audio
  9. Gradient-based learning applied to document recognition
  10. Long Short-Term Memory

Their papers