Shanika A. Karunasekera

Artificial Intelligence · 2010–2016

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it; #23,874 of 35,345 by trust here, #13,760 by citations
• Computer Networks and Communications — 25 citations into it; #6,289 of 9,886 by trust here, #2,539 by citations
• Signal Processing — 20 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it; #14,760 of 21,575 by trust here, #10,154 by citations
• Information Systems — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Shanika A. Karunasekera trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Frédéric Cuppens
4. Yann LeCun
5. Lawrence R. Rabiner
6. Yuhai Wu
7. Chih-Jen Lin
8. Anukool Lakhina
9. Yichuan Tang
10. Alex Krizhevsky

Who trusts Shanika A. Karunasekera overall

1. Lukas Ruff
2. Raghavendra Chalapathy
3. Nivedita Mishra

Papers from Shanika A. Karunasekera's perspective

Ordered by how strongly the researchers Shanika A. Karunasekera 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
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

• High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning (2016) — 1,120 citations
• A survey of coordinated attacks and collaborative intrusion detection (2010) — 407 citations