Surya Ganguli

According to our database1, Surya Ganguli authored at least 59 papers between 2010 and 2021.

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Bibliography

2021
Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion.
CoRR, 2021

Deep Learning on a Data Diet: Finding Important Examples Early in Training.
CoRR, 2021

How many degrees of freedom do we need to train deep networks: a loss landscape perspective.
CoRR, 2021

Embodied Intelligence via Learning and Evolution.
CoRR, 2021

Understanding self-supervised learning dynamics without contrastive pairs.
Proceedings of the 38th International Conference on Machine Learning, 2021

A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions.
Proceedings of the 38th International Conference on Machine Learning, 2021

Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Fundamental bounds on the fidelity of sensory cortical coding.
Nat., 2020

Understanding Self-supervised Learning with Dual Deep Networks.
CoRR, 2020

Pruning neural networks without any data by iteratively conserving synaptic flow.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Identifying Learning Rules From Neural Network Observables.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Predictive coding in balanced neural networks with noise, chaos and delays.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Two Routes to Scalable Credit Assignment without Weight Symmetry.
Proceedings of the 37th International Conference on Machine Learning, 2020

RNNs can generate bounded hierarchical languages with optimal memory.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
Emergent properties of the local geometry of neural loss landscapes.
CoRR, 2019

Fast Convolutive Nonnegative Matrix Factorization Through Coordinate and Block Coordinate Updates.
CoRR, 2019

From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A unified theory for the origin of grid cells through the lens of pattern formation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Universality and individuality in neural dynamics across large populations of recurrent networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs.
Proceedings of the 7th International Conference on Learning Representations, 2019

An analytic theory of generalization dynamics and transfer learning in deep linear networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Inferring hidden structure in multilayered neural circuits.
PLoS Comput. Biol., 2018

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

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

The emergence of multiple retinal cell types through efficient coding of natural movies.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Task-Driven Convolutional Recurrent Models of the Visual System.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Statistical mechanics of low-rank tensor decomposition.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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 Softw., 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

Deep Information Propagation.
Proceedings of the 5th International Conference on Learning Representations, 2017

Intelligent synapses for multi-task and transfer learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Survey of Expressivity in Deep Neural Networks.
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.
Frontiers Comput. Neurosci., 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
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.
Proceedings of the 2nd International Conference on Learning Representations, 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.
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

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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