Srinivasan Parthasarathy

Artificial Intelligence · 1997–2019

A researcher in the Science corpus: 9 papers; trusts 94 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 84 citations into it; #17,917 of 35,345 by trust here, #18,586 by citations
• Statistical and Nonlinear Physics — 40 citations into it; #2,497 of 10,127 by trust here, #3,010 by citations
• Molecular Biology — 37 citations into it; #8,571 of 17,773 by trust here, #12,742 by citations
• Natural Language Processing — 31 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Graph Learning — 19 citations into it
• Computational Theory and Mathematics — 14 citations into it
• Information Systems — 12 citations into it

Whom Srinivasan Parthasarathy trusts overall

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

1. Mark Newman
2. Rakesh Agrawal
3. Geoffrey E. Hinton
4. Jon M. Kleinberg
5. Diederik P. Kingma
6. Yoshua Bengio
7. Jure Leskovec
8. Alex Krizhevsky
9. Dekang Lin
10. Ilya Sutskever

Who trusts Srinivasan Parthasarathy overall

1. Christian Borgelt
2. Mohammed J. Zaki
3. Bart Goethals
4. Fadi A. Thabtah
5. Siegfried Nijssen
6. Giulio Rossetti
7. Tong Wang
8. Aaron Ceglar
9. Yu-Ru Lin
10. Derek Greene

Papers from Srinivasan Parthasarathy's perspective

Ordered by how strongly the researchers Srinivasan Parthasarathy 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Dependent rounding and its applications to approximation algorithms (2006) — 346 citations
• Graph embedding on biomedical networks: methods, applications and evaluations (2019) — 370 citations
• Local Probabilistic Models for Link Prediction (2007) — 357 citations
• An event-based framework for characterizing the evolutionary behavior of interaction graphs (2007) — 435 citations
• Towards Open Intent Discovery for Conversational Text (2019) — 27 citations
• Proceedings of the 2013 SIAM International Conference on Data Mining (2013) — 45 citations
• Efficient community detection in large networks using content and links (2012) — 332 citations
• Automated Decision Tree Classification of Corneal Shape (2005) — 111 citations
• New Algorithms for Fast Discovery of Association Rules (1997)