Thomas Powers

Model Architectures · 2016

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Powers trusts overall

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

  1. Yoshua Bengio
  2. Robert Tibshirani
  3. Geoffrey E. Hinton
  4. Sepp Hochreiter
  5. Yann LeCun
  6. Martín Arjovsky
  7. Xavier Glorot
  8. Kaiming He
  9. Quoc V. Le
  10. Hemant D. Tagare

Who trusts Thomas Powers overall

  1. Shaojie Bai
  2. J. Tomczak
  3. Piotr A. Sokól
  4. Mario Lezcano Casado
  5. Tolga Ergen
  6. Shuai Li
  7. Weixin Luo
  8. Lei Huang
  9. Cem Anil
  10. Jun Li

Papers from Thomas Powers's perspective

Ordered by how strongly the researchers Thomas Powers 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. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet: A large-scale hierarchical image database
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers