Nipun Kwatra

Artificial Intelligence · 2005–2024

A researcher in the Science corpus: 4 papers; trusts 36 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Computer Vision and Pattern Recognition — 48 citations into it; #8,519 of 21,575 by trust here, #9,722 by citations
• Model Architectures — 17 citations into it
• Computer Networks and Communications — 15 citations into it
• Computer Graphics and Computer-Aided Design — 9 citations into it; #517 of 1,584 by trust here, #558 by citations
• Hardware and Architecture — 7 citations into it

Whom Nipun Kwatra trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Alexei A. Efros
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Yoshua Bengio
7. Ilya Sutskever
8. Jeremy S. De Bonet
9. Charles Peter Elkan
10. Yann LeCun

Who trusts Nipun Kwatra overall

1. Nikos Komodakis
2. Chuan Li
3. Joan Bruna
4. Raanan Fattal

Papers from Nipun Kwatra's perspective

Ordered by how strongly the researchers Nipun Kwatra 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. ImageNet: A large-scale hierarchical image database
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Texture optimization for example-based synthesis (2005) — 770 citations
• Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve (2024) — 640 citations
• Balancing efficiency and fairness in heterogeneous GPU clusters for deep learning (2020) — 173 citations
• Gandiva: Introspective Cluster Scheduling for Deep Learning (2018) — 605 citations