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A biologically plausible neural network for multi-channel Canonical Correlation Analysis

Oct 01, 2020
David Lipshutz, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta, Dmitri B. Chkovskii

* 34 pages, 8 figures 

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Emergent Structures and Lifetime Structure Evolution in Artificial Neural Networks

Nov 26, 2019
Siavash Golkar

* Proceedings of NeurIPS workshop on Real Neurons & Hidden Units. 5 Pages, 6 figures 

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Task-Driven Data Verification via Gradient Descent

May 14, 2019
Siavash Golkar, Kyunghyun Cho

* 10 pages, 6 figures 

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Inferring the quantum density matrix with machine learning

Apr 11, 2019
Kyle Cranmer, Siavash Golkar, Duccio Pappadopulo

* 12 pages, 3 figures 

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Continual Learning via Neural Pruning

Mar 11, 2019
Siavash Golkar, Michael Kagan, Kyunghyun Cho

* 12 pages, 5 figures, 3 tables 

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Backdrop: Stochastic Backpropagation

Jun 04, 2018
Siavash Golkar, Kyle Cranmer

* 11 pages, 9 figures, 2 tables. Source code available at https://github.com/dexgen/backdrop 

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