Varun Chandola

Artificial Intelligence · 2008–2012

A researcher in the Science corpus: 3 papers; trusts 67 researchers and is trusted by 93 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it; #3,009 of 35,345 by trust here, #2,989 by citations
• Computer Networks and Communications — 32 citations into it; #352 of 9,886 by trust here, #223 by citations
• Signal Processing — 31 citations into it
• Information Systems — 9 citations into it
• Biomedical Engineering — 7 citations into it; #4,428 of 10,734 by trust here, #6,312 by citations
• Computer Vision and Pattern Recognition — 6 citations into it
• Economics and Econometrics — 6 citations into it
• Civil and Structural Engineering — 5 citations into it

Whom Varun Chandola trusts overall

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

1. Eamonn J. Keogh
2. Eleazar Eskin
3. Stephanie Forrest
4. Anil K. Jain
5. Stefano Lonardi
6. Vladimir Naumovich Vapni
7. William W. Cohen
8. Nong Ye
9. Christina E. Warrender
10. Jessica Lin

Who trusts Varun Chandola overall

1. Charu C. Aggarwal
2. Leman Akoglu
3. Markus Goldstein
4. Andreas Holzinger
5. Lukas Ruff
6. Leying Guan
7. Nicolas Papernot
8. John Alexander Quinn
9. Alexander Lavin
10. B. Vo

Papers from Varun Chandola's perspective

Ordered by how strongly the researchers Varun Chandola 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Going deeper with convolutions
10. Et al

Their papers

• Anomaly detection: A survey (2009) — 12,600 citations
• Similarity Measures for Categorical Data: A Comparative Evaluation (2008) — 662 citations
• Anomaly Detection for Discrete Sequences: A Survey (2012) — 633 citations