Surya Ganguli

According to our database1, Surya Ganguli authored at least 42 papers between 2010 and 2018.

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Bibliography

2018
SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.
Neural Computation, 2018

A mathematical theory of semantic development in deep neural networks.
CoRR, 2018

Statistical mechanics of low-rank tensor decomposition.
CoRR, 2018

An analytic theory of generalization dynamics and transfer learning in deep linear networks.
CoRR, 2018

Task-Driven Convolutional Recurrent Models of the Visual System.
CoRR, 2018

The Emergence of Spectral Universality in Deep Networks.
CoRR, 2018

The emergence of spectral universality in deep networks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Pyret: A Python package for analysis of neurophysiology data.
J. Open Source Software, 2017

Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice.
CoRR, 2017

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net.
CoRR, 2017

Improved multitask learning through synaptic intelligence.
CoRR, 2017

SuperSpike: Supervised learning in multi-layer spiking neural networks.
CoRR, 2017

Biologically inspired protection of deep networks from adversarial attacks.
CoRR, 2017

Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Continual Learning Through Synaptic Intelligence.
Proceedings of the 34th International Conference on Machine Learning, 2017

On the Expressive Power of Deep Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Deep Information Propagation.
CoRR, 2016

Survey of Expressivity in Deep Neural Networks.
CoRR, 2016

On the expressive power of deep neural networks.
CoRR, 2016

Exponential expressivity in deep neural networks through transient chaos.
CoRR, 2016

A universal tradeoff between power, precision and speed in physical communication.
CoRR, 2016

Random projections of random manifolds.
CoRR, 2016

Exponential expressivity in deep neural networks through transient chaos.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Deep Learning Models of the Retinal Response to Natural Scenes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

An equivalence between high dimensional Bayes optimal inference and M-estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences.
Front. Comput. Neurosci., 2015

Deep Unsupervised Learning using Nonequilibrium Thermodynamics.
CoRR, 2015

Deep Knowledge Tracing.
CoRR, 2015

Deep Knowledge Tracing.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Deep Unsupervised Learning using Nonequilibrium Thermodynamics.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Analyzing noise in autoencoders and deep networks.
CoRR, 2014

On the saddle point problem for non-convex optimization.
CoRR, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
CoRR, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
An adaptive low dimensional quasi-Newton sum of functions optimizer.
CoRR, 2013

Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.
CoRR, 2013

A memory frontier for complex synapses.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Investigating the role of firing-rate normalization and dimensionality reduction in brain-machine interface robustness.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

Learning hierarchical categories in deep neural networks.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2010
Short-term memory in neuronal networks through dynamical compressed sensing.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010


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