Prannoy Pilligundla

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Efficiency & Compression — 9 citations into it
• Optimization & Training — 7 citations into it

Whom Prannoy Pilligundla trusts overall

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

1. Barret Zoph
2. John Schulman
3. Yihui He
4. Quoc V. Le
5. Song Han
6. Alex Krizhevsky
7. Geoffrey E. Hinton
8. Yoshua Bengio
9. Kaiming He
10. Patrick Judd

Who trusts Prannoy Pilligundla overall

1. Alexandre D'efossez
2. Qing Jin
3. Sein Park

Papers from Prannoy Pilligundla's perspective

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

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

Their papers

• ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks (2020) — 61 citations
• ReLeQ: An Automatic Reinforcement Learning Approach for Deep Quantization of Neural Networks (2018)