Anirvan M. Sengupta

50 papers A* 8B 1Journal 36Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation. AAAI Shanshan Qin, Joshua Pughe-Sanford, Alexander Genkin, Pembe Gizem Özdil, Philip Greengard, Anirvan M. Sengupta, Dmitri B. Chklovskii
2025	A*	`conf`	In-Context Denoising with One-Layer Transformers: Connections between Attention and Associative Memory Retrieval. ICML Matthew Smart, Alberto Bietti, Anirvan M. Sengupta
2025	J	`jnl`	In-context denoising with one-layer transformers: connections between attention and associative memory retrieval. CoRR Matthew Smart, Alberto Bietti, Anirvan M. Sengupta
2024	J	`jnl`	Deep Learning Based Superconductivity: Prediction and Experimental Tests. CoRR Daniel Kaplan, Adam Zhang, Joanna Blawat, Rongying Jin, Robert J. Cava, Viktor Oudovenko, Gabriel Kotliar, Anirvan M. Sengupta, Weiwei Xie
2024	J	`jnl`	Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function. Mach. Learn. Sci. Technol. Jiawei Zang, Matija Medvidovic, Dominik Kiese, Domenico Di Sante, Anirvan M. Sengupta, Andrew J. Millis
2023	J	`jnl`	A normative framework for deriving neural networks with multi-compartmental neurons and non-Hebbian plasticity. CoRR David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii
2023	J	`jnl`	Duality Principle and Biologically Plausible Learning: Connecting the Representer Theorem and Hebbian Learning. CoRR Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
2023	J	`jnl`	Unlocking the Potential of Similarity Matching: Scalability, Supervision and Pre-training. CoRR Yanis Bahroun, Shagesh Sridharan, Atithi Acharya, Dmitri B. Chklovskii, Anirvan M. Sengupta
2022	A*	`conf`	Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy. NeurIPS Siavash Golkar, Tiberiu Tesileanu, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
2022	J	`jnl`	Neural Circuits for Dynamics-Based Segmentation of Time Series. Neural Comput. Tiberiu Tesileanu, Siavash Golkar, Samaneh Nasiri, Anirvan M. Sengupta, Dmitri B. Chklovskii
2022	—	`conf`	Spatial Transformer K-Means. IEEECONF Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
2022	J	`jnl`	Spatial Transformer K-Means. CoRR Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
2022	J	`jnl`	Toward a Geometrical Understanding of Self-supervised Contrastive Learning. CoRR Romain Cosentino, Anirvan M. Sengupta, Salman Avestimehr, Mahdi Soltanolkotabi, Antonio Ortega, Theodore L. Willke, Mariano Tepper
2021	J	`jnl`	A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis. Neural Comput. David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii
2021	A*	`conf`	A Normative and Biologically Plausible Algorithm for Independent Component Analysis. NeurIPS Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
2021	J	`jnl`	A Normative and Biologically Plausible Algorithm for Independent Component Analysis. CoRR Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
2021	J	`jnl`	A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit. CoRR Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
2021	J	`jnl`	Informationally complete POVM-based shadow tomography. CoRR Atithi Acharya, Siddhartha Saha, Anirvan M. Sengupta
2021	A*	`conf`	Neural optimal feedback control with local learning rules. NeurIPS Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
2021	J	`jnl`	Neural optimal feedback control with local learning rules. CoRR Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
2020	J	`jnl`	A biologically plausible neural network for local supervision in cortical microcircuits. CoRR Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
2020	J	`jnl`	A biologically plausible neural network for multi-channel Canonical Correlation Analysis. CoRR David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chklovskii
2020	A*	`conf`	A simple normative network approximates local non-Hebbian learning in the cortex. NeurIPS Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
2020	J	`jnl`	A simple normative network approximates local non-Hebbian learning in the cortex. CoRR Siavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
2020	J	`jnl`	Interpretable Image Clustering via Diffeomorphism-Aware K-Means. CoRR Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
2020	J	`jnl`	Neurons as Canonical Correlation Analyzers. Frontiers Comput. Neurosci. Cengiz Pehlevan, Xinyuan Zhao, Anirvan M. Sengupta, Dmitri B. Chklovskii
2019	J	`jnl`	A Neural Network for Semi-Supervised Learning on Manifolds. CoRR Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
2019	—	`conf`	A Neural Network for Semi-supervised Learning on Manifolds. ICANN (1) Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii
2019	A*	`conf`	A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit. NeurIPS Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta
2018	J	`jnl`	Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling. J. Mach. Learn. Res. Mariano Tepper, Anirvan M. Sengupta, Dmitri B. Chklovskii
2018	A*	`conf`	Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks. NeurIPS Anirvan M. Sengupta, Cengiz Pehlevan, Mariano Tepper, Alexander Genkin, Dmitri B. Chklovskii
2018	J	`jnl`	Why Do Similarity Matching Objectives Lead to Hebbian/Anti-Hebbian Networks? Neural Comput. Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii
2017	J	`jnl`	Adversarial synapses: Hebbian/anti-Hebbian learning optimizes min-max objectives. CoRR Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii
2017	—	`conf`	Resource-efficient perceptron has sparse synaptic weight distribution. SIU Cengiz Pehlevan, Anirvan M. Sengupta
2017	J	`jnl`	The surprising secret identity of the semidefinite relaxation of K-means: manifold learning. CoRR Mariano Tepper, Anirvan M. Sengupta, Dmitri B. Chklovskii
2016	—	`conf`	Mean field analysis of sparse reconstruction with correlated variables. EUSIPCO Mohammad Ramezanali, Partha P. Mitra, Anirvan M. Sengupta
2015	J	`jnl`	Critical behavior and universality classes for an algorithmic phase transition in sparse reconstruction. CoRR Mohammad Ramezanali, Partha P. Mitra, Anirvan M. Sengupta
2015	J	`jnl`	The cavity method for phase transitions in sparse reconstruction algorithms. CoRR Mohammad Ramezanali, Partha P. Mitra, Anirvan M. Sengupta
2013	J	`jnl`	The Role of Multiple Marks in Epigenetic Silencing and the Emergence of a Stable Bivalent Chromatin State. PLoS Comput. Biol. Swagatam Mukhopadhyay, Anirvan M. Sengupta
2012	J	`jnl`	SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding. J. Comput. Biol. Rajat Shuvro Roy, Kevin C. Chen, Anirvan M. Sengupta, Alexander Schliep
2011	J	`jnl`	Does the Potential for Chaos Constrain the Embryonic Cell-Cycle Oscillator? PLoS Comput. Biol. R. Scott McIsaac, Kerwyn Casey Huang, Anirvan M. Sengupta, Ned S. Wingreen
2011	J	`jnl`	SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding CoRR Rajat Shuvro Roy, Kevin C. Chen, Anirvan M. Sengupta, Alexander Schliep
2010	J	`jnl`	Locus dependence in epigenetic chromatin silencing. Biosyst. Swagatam Mukhopadhyay, Vijayalakshmi H. Nagaraj, Anirvan M. Sengupta
2010	J	`jnl`	SOPRA: Scaffolding algorithm for paired reads via statistical optimization. BMC Bioinform. Adel Dayarian, Todd P. Michael, Anirvan M. Sengupta
2009	J	`jnl`	OHMM: a Hidden Markov Model accurately predicting the occupancy of a transcription factor with a self-overlapping binding motif. BMC Bioinform. Amar Drawid, Nupur Gupta, Vijayalakshmi H. Nagaraj, Céline Gélinas, Anirvan M. Sengupta
2009	J	`jnl`	Shape, Size, and Robustness: Feasible Regions in the Parameter Space of Biochemical Networks. PLoS Comput. Biol. Adel Dayarian, Madalena Chaves, Eduardo D. Sontag, Anirvan M. Sengupta
2005	J	`jnl`	Non-additivity in protein-DNA binding. Bioinform. Ruadhan A. O'Flanagan, Guillaume Paillard, Richard Lavery, Anirvan M. Sengupta
2003	B	`conf`	A model to calculate the capacity distribution of correlated MIMO channels and interferers. GLOBECOM Aris L. Moustakas, Steven H. Simon, Anirvan M. Sengupta
2003	—	`conf`	Distribution of MIMO capacity in the presence of correlated signals and interferers: A (not so) large N analysis. Multiantenna Channels: Capacity, Coding and Signal Processing Aris L. Moustakas, Steven H. Simon, Anirvan M. Sengupta
2003	J	`jnl`	MIMO capacity through correlated channels in the presence of correlated interferers and noise: a (not so) large N analysis. IEEE Trans. Inf. Theory Aris L. Moustakas, Steven H. Simon, Anirvan M. Sengupta