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Fingerprint Dive into the research topics where Anirvan Sengupta is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Chromatin Medicine & Life Sciences
Epigenomics Medicine & Life Sciences
Transcription Factors Medicine & Life Sciences
Binding Sites Medicine & Life Sciences
Yeasts Medicine & Life Sciences
DNA Medicine & Life Sciences
Gene Regulatory Networks Medicine & Life Sciences
SELEX Aptamer Technique Medicine & Life Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2006 2011

Genome
Transcription Factors
Escherichia coli
Sigma Factor
Gene Expression
Genome
Transcription Factors
Escherichia coli
Sigma Factor
Gene Expression

Research Output 1994 2019

A Neural Network for Semi-supervised Learning on Manifolds

Sengupta, A. M., Jan 1 2019, Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings. Tetko, I. V., Karpov, P., Theis, F. & Kurková, V. (eds.). Springer Verlag, p. 375-386 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11727 LNCS).

Rutgers, The State University

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Semi-supervised Learning
Supervised learning
Neural Networks
Neural networks
Feedforward neural networks
Critical Behavior
Mean Squared Error
Universality
Critical Curves
Phase Transition
Semidefinite Program
Manifold Learning
Non-negative
Clustering
Gradient methods
preserving
neurons
brain
hippocampus
rodents
9 Citations (Scopus)

Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks?

Sengupta, A., Jan 1 2018, In : Neural computation. 30, 1, p. 84-124 41 p.

Rutgers, The State University

Research output: Contribution to journalArticle

Learning
Intuition
Neurosciences
Synapses
History