Niladrish Chatterjee

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 24 citations into it
• Efficiency & Compression — 16 citations into it
• Model Architectures — 8 citations into it

Whom Niladrish Chatterjee trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Yoshua Bengio
6. Sepp Hochreiter
7. J. Urgen Schmidhuber
8. Ilya Sutskever
9. Christian Szegedy
10. Andrew Zisserman

Papers from Niladrish Chatterjee's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Going deeper with convolutions
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks (2017) — 193 citations