Sudipto Mukherjee

Affiliations:
  • University of Washington, Department of Electrical & Computer Engineering, Seattle, WA, USA
  • Jadavpur University, Department of Electronics and Telecommunication Engineering, Kolkata, India (former)


According to our database1, Sudipto Mukherjee authored at least 14 papers between 2013 and 2020.

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Bibliography

2020
Unsupervised Learning : Model-guided and Model-agnostic Approaches.
PhD thesis, 2020

C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation.
CoRR, 2020

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis.
BMC Bioinform., 2020

C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Smart To-Do: Automatic Generation of To-Do Items from Emails.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
A Content-Based Approach to Email Triage Action Prediction: Exploration and Evaluation.
CoRR, 2019

CCMI : Classifier based Conditional Mutual Information Estimation.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

ClusterGAN: Latent Space Clustering in Generative Adversarial Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017
Variants of k-regular nearest neighbor graph and their construction.
Inf. Process. Lett., 2017

Resolving Multicopy Duplications de novo Using Polyploid Phasing.
Proceedings of the Research in Computational Molecular Biology, 2017

2015
A Lagrangian Approach to Modeling and Analysis of a Crowd Dynamics.
IEEE Trans. Syst. Man Cybern. Syst., 2015

2014
Behavioral analysis of the leader particle during stagnation in a particle swarm optimization algorithm.
Inf. Sci., 2014

Stability and chaos analysis of a novel swarm dynamics with applications to multi-agent systems.
Eng. Appl. Artif. Intell., 2014

2013
Differential Evolution with Controlled Annihilation and Regeneration of Individuals and A Novel Mutation Scheme.
Proceedings of the Swarm, Evolutionary, and Memetic Computing, 2013


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