Anirvan M. Sengupta
According to our database1,
Anirvan M. Sengupta
authored at least 39 papers
between 2003 and 2023.
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Bibliography
2023
Duality Principle and Biologically Plausible Learning: Connecting the Representer Theorem and Hebbian Learning.
CoRR, 2023
Unlocking the Potential of Similarity Matching: Scalability, Supervision and Pre-training.
CoRR, 2023
A normative framework for deriving neural networks with multi-compartmental neurons and non-Hebbian plasticity.
CoRR, 2023
2022
CoRR, 2022
Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022
2021
A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis.
Neural Comput., 2021
A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
A biologically plausible neural network for local supervision in cortical microcircuits.
CoRR, 2020
A biologically plausible neural network for multi-channel Canonical Correlation Analysis.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019
2018
Neural Comput., 2018
Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling.
J. Mach. Learn. Res., 2018
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
The surprising secret identity of the semidefinite relaxation of K-means: manifold learning.
CoRR, 2017
CoRR, 2017
Proceedings of the 25th Signal Processing and Communications Applications Conference, 2017
2016
Proceedings of the 24th European Signal Processing Conference, 2016
2015
Critical behavior and universality classes for an algorithmic phase transition in sparse reconstruction.
CoRR, 2015
CoRR, 2015
2013
The Role of Multiple Marks in Epigenetic Silencing and the Emergence of a Stable Bivalent Chromatin State.
PLoS Comput. Biol., 2013
2012
J. Comput. Biol., 2012
2011
PLoS Comput. Biol., 2011
2010
BMC Bioinform., 2010
2009
Shape, Size, and Robustness: Feasible Regions in the Parameter Space of Biochemical Networks.
PLoS Comput. Biol., 2009
OHMM: a Hidden Markov Model accurately predicting the occupancy of a transcription factor with a self-overlapping binding motif.
BMC Bioinform., 2009
2005
2003
MIMO capacity through correlated channels in the presence of correlated interferers and noise: a (not so) large N analysis.
IEEE Trans. Inf. Theory, 2003
A model to calculate the capacity distribution of correlated MIMO channels and interferers.
Proceedings of the Global Telecommunications Conference, 2003
Distribution of MIMO capacity in the presence of correlated signals and interferers: A (not so) large N analysis.
Proceedings of the Multiantenna Channels: Capacity, 2003