Adrian Kim

Signal Processing · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Adrian Kim trusts overall

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

  1. Andrew L. Maas

Papers from Adrian Kim's perspective

Ordered by how strongly the researchers Adrian Kim trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Understanding the difficulty of training deep feedforward neural networks
  2. ImageNet classification with deep convolutional neural networks
  3. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Rectifier Nonlinearities Improve Neural Network Acoustic Models
  8. Gradient-based learning applied to document recognition
  9. Signal estimation from modified short-time Fourier transform
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers