Surya Ganguli - RankMe

127 papers A* 34A 1B 1Journal 75Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Causal Interpretation of Neural Network Computations with Contribution Decomposition. CoRR Joshua Melander, Zaki Alaoui, Shenghua Liu, Surya Ganguli, Stephen A. Baccus
2026	J	`jnl`	Contrastive Concept-Tree Search for LLM-Assisted Algorithm Discovery. CoRR Timothee Leleu, Sudeera Gunathilaka, Federico Ghimenti, Surya Ganguli
2026	J	`jnl`	Deriving Neural Scaling Laws from the statistics of natural language. CoRR Francesco Cagnetta, Allan Raventós, Surya Ganguli, Matthieu Wyart
2026	J	`jnl`	From Kepler to Newton: Inductive Biases Guide Learned World Models in Transformers. CoRR Ziming Liu, Sophia Sanborn, Surya Ganguli, Andreas S. Tolias
2026	J	`jnl`	Solving adversarial examples requires solving exponential misalignment. CoRR Alessandro Salvatore, Stanislav Fort, Surya Ganguli
2025	J	`jnl`	Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks. CoRR Daniel Kunin, Giovanni Luca Marchetti, Feng Chen, Dhruva Karkada, James B. Simon, Michael Robert DeWeese, Surya Ganguli, Nina Miolane
2025	A*	`conf`	An analytic theory of creativity in convolutional diffusion models. ICML Mason Kamb, Surya Ganguli
2025	J	`jnl`	CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers. CoRR Haining Pan, James V. Roggeveen, Erez Berg, Juan Carrasquilla, Debanjan Chowdhury, Surya Ganguli, Federico Ghimenti, Juraj Hasik, Henry Hunt, HongJiang Zhang, Mason Kamb, Ying-Jer Kao, Ehsan Khatami, Michael J. Lawler, Di Luo, Titus Neupert, Xiaoliang Qi, Michael P. Brenner, Eun-Ah Kim
2025	A*	`conf`	Features are fate: a theory of transfer learning in high-dimensional regression. ICML Javan Tahir, Surya Ganguli, Grant M. Rotskoff
2025	J	`jnl`	Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning. CoRR Feng Chen, Allan Raventós, Nan Cheng, Surya Ganguli, Shaul Druckmann
2024	J	`jnl`	An analytic theory of creativity in convolutional diffusion models. CoRR Mason Kamb, Surya Ganguli
2024	J	`jnl`	Features are fate: a theory of transfer learning in high-dimensional regression. CoRR Javan Tahir, Surya Ganguli, Grant M. Rotskoff
2024	J	`jnl`	Fooling LLM graders into giving better grades through neural activity guided adversarial prompting. CoRR Atsushi Yamamura, Surya Ganguli
2024	J	`jnl`	Geometric Dynamics of Signal Propagation Predict Trainability of Transformers. CoRR Aditya Cowsik, Tamra Nebabu, Xiao-Liang Qi, Surya Ganguli
2024	A*	`conf`	Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning. NeurIPS Daniel Kunin, Allan Raventós, Clémentine C. J. Dominé, Feng Chen, David A. Klindt, Andrew M. Saxe, Surya Ganguli
2024	J	`jnl`	Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning. CoRR Daniel Kunin, Allan Raventós, Clémentine C. J. Dominé, Feng Chen, David A. Klindt, Andrew M. Saxe, Surya Ganguli
2024	J	`jnl`	The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion. Neural Comput. Daniel Kunin, Javier Sagastuy-Breña, Lauren E. Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
2023	A*	`conf`	Disentanglement with Biological Constraints: A Theory of Functional Cell Types. ICLR James C. R. Whittington, Will Dorrell, Surya Ganguli, Timothy Behrens
2023	J	`jnl`	Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
2023	A*	`conf`	Information Geometry of the Retinal Representation Manifold. NeurIPS Xuehao Ding, Dongsoo Lee, Joshua Melander, George Sivulka, Surya Ganguli, Stephen Baccus
2023	A*	`conf`	Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression. NeurIPS Allan Raventós, Mansheej Paul, Feng Chen, Surya Ganguli
2023	J	`jnl`	Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression. CoRR Allan Raventós, Mansheej Paul, Feng Chen, Surya Ganguli
2023	J	`jnl`	SemDeDup: Data-efficient learning at web-scale through semantic deduplication. CoRR Amro Abbas, Kushal Tirumala, Daniel Simig, Surya Ganguli, Ari S. Morcos
2023	A*	`conf`	Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks. NeurIPS Feng Chen, Daniel Kunin, Atsushi Yamamura, Surya Ganguli
2023	J	`jnl`	Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks. CoRR Feng Chen, Daniel Kunin, Atsushi Yamamura, Surya Ganguli
2023	A*	`conf`	The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks. ICLR Daniel Kunin, Atsushi Yamamura, Chao Ma, Surya Ganguli
2023	A*	`conf`	Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? ICLR Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite
2022	A*	`conf`	Beyond neural scaling laws: beating power law scaling via data pruning. NeurIPS Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari Morcos
2022	J	`jnl`	Beyond neural scaling laws: beating power law scaling via data pruning. CoRR Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari S. Morcos
2022	J	`jnl`	Disentangling with Biological Constraints: A Theory of Functional Cell Types. CoRR James C. R. Whittington, Will Dorrell, Surya Ganguli, Timothy Edward John Behrens
2022	J	`jnl`	Holistic Evaluation of Language Models. CoRR Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
2022	A*	`conf`	How many degrees of freedom do we need to train deep networks: a loss landscape perspective. ICLR Brett W. Larsen, Stanislav Fort, Nic Becker, Surya Ganguli
2022	A*	`conf`	Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. NeurIPS Mansheej Paul, Brett W. Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite
2022	J	`jnl`	Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. CoRR Mansheej Paul, Brett W. Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite
2022	A*	`conf`	MetaMorph: Learning Universal Controllers with Transformers. ICLR Agrim Gupta, Linxi Fan, Surya Ganguli, Li Fei-Fei
2022	J	`jnl`	MetaMorph: Learning Universal Controllers with Transformers. CoRR Agrim Gupta, Linxi Fan, Surya Ganguli, Li Fei-Fei
2022	J	`jnl`	Optimal noise level for coding with tightly balanced networks of spiking neurons in the presence of transmission delays. PLoS Comput. Biol. Jonathan Timcheck, Jonathan Kadmon, Kwabena Boahen, Surya Ganguli
2022	J	`jnl`	Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition. Neural Comput. Aran Nayebi, Javier Sagastuy-Breña, Daniel M. Bear, Kohitij Kar, Jonas Kubilius, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2022	J	`jnl`	Synaptic balancing: A biologically plausible local learning rule that provably increases neural network noise robustness without sacrificing task performance. PLoS Comput. Biol. Christopher H. Stock, Sarah E. Harvey, Samuel A. Ocko, Surya Ganguli
2022	J	`jnl`	The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks. CoRR Daniel Kunin, Atsushi Yamamura, Chao Ma, Surya Ganguli
2022	J	`jnl`	Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao
2022	J	`jnl`	Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? CoRR Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite
2022	J	`jnl`	What does a deep neural network confidently perceive? The effective dimension of high certainty class manifolds and their low confidence boundaries. CoRR Stanislav Fort, Ekin Dogus Cubuk, Surya Ganguli, Samuel S. Schoenholz
2021	A*	`conf`	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. ICML Gabriel Mel, Surya Ganguli
2021	A*	`conf`	Deep Learning on a Data Diet: Finding Important Examples Early in Training. NeurIPS Mansheej Paul, Surya Ganguli, Gintare Karolina Dziugaite
2021	J	`jnl`	Deep Learning on a Data Diet: Finding Important Examples Early in Training. CoRR Mansheej Paul, Surya Ganguli, Gintare Karolina Dziugaite
2021	J	`jnl`	Embodied Intelligence via Learning and Evolution. CoRR Agrim Gupta, Silvio Savarese, Surya Ganguli, Li Fei-Fei
2021	A*	`conf`	Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks. NeurIPS Aran Nayebi, Alexander Attinger, Malcolm Campbell, Kiah Hardcastle, Isabel Low, Caitlin S. Mallory, Gabriel Mel, Ben Sorscher, Alex H. Williams, Surya Ganguli, Lisa M. Giocomo, Daniel L. K. Yamins
2021	J	`jnl`	How many degrees of freedom do we need to train deep networks: a loss landscape perspective. CoRR Brett W. Larsen, Stanislav Fort, Nic Becker, Surya Ganguli
2021	A*	`conf`	Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics. ICLR Daniel Kunin, Javier Sagastuy-Breña, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka
2021	J	`jnl`	Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion. CoRR Daniel Kunin, Javier Sagastuy-Breña, Lauren E. Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
2021	J	`jnl`	Understanding self-supervised Learning Dynamics without Contrastive Pairs. CoRR Yuandong Tian, Xinlei Chen, Surya Ganguli
2021	A*	`conf`	Understanding self-supervised learning dynamics without contrastive pairs. ICML Yuandong Tian, Xinlei Chen, Surya Ganguli
2020	A*	`conf`	Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel. NeurIPS Stanislav Fort, Gintare Karolina Dziugaite, Mansheej Paul, Sepideh Kharaghani, Daniel M. Roy, Surya Ganguli
2020	J	`jnl`	Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel. CoRR Stanislav Fort, Gintare Karolina Dziugaite, Mansheej Paul, Sepideh Kharaghani, Daniel M. Roy, Surya Ganguli
2020	J	`jnl`	Fundamental bounds on the fidelity of sensory cortical coding. Nat. Oleg I. Rumyantsev, Jérôme A. Lecoq, Oscar Hernandez, Yanping Zhang, Joan Savall, Radoslaw Chrapkiewicz, Jane Li, Hongkui Zeng, Surya Ganguli, Mark J. Schnitzer
2020	A*	`conf`	Identifying Learning Rules From Neural Network Observables. NeurIPS Aran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L. K. Yamins
2020	J	`jnl`	Identifying Learning Rules From Neural Network Observables. CoRR Aran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L. K. Yamins
2020	J	`jnl`	Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics. CoRR Daniel Kunin, Javier Sagastuy-Breña, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka
2020	A*	`conf`	Predictive coding in balanced neural networks with noise, chaos and delays. NeurIPS Jonathan Kadmon, Jonathan Timcheck, Surya Ganguli
2020	A*	`conf`	Pruning neural networks without any data by iteratively conserving synaptic flow. NeurIPS Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli
2020	J	`jnl`	Pruning neural networks without any data by iteratively conserving synaptic flow. CoRR Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli
2020	—	`conf`	RNNs can generate bounded hierarchical languages with optimal memory. EMNLP (1) John Hewitt, Michael Hahn, Surya Ganguli, Percy Liang, Christopher D. Manning
2020	J	`jnl`	RNNs can generate bounded hierarchical languages with optimal memory. CoRR John Hewitt, Michael Hahn, Surya Ganguli, Percy Liang, Christopher D. Manning
2020	A*	`conf`	Two Routes to Scalable Credit Assignment without Weight Symmetry. ICML Daniel Kunin, Aran Nayebi, Javier Sagastuy-Breña, Surya Ganguli, Jonathan M. Bloom, Daniel Yamins
2020	J	`jnl`	Two Routes to Scalable Credit Assignment without Weight Symmetry. CoRR Daniel Kunin, Aran Nayebi, Javier Sagastuy-Breña, Surya Ganguli, Jonathan M. Bloom, Daniel L. K. Yamins
2020	J	`jnl`	Understanding Self-supervised Learning with Dual Deep Networks. CoRR Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli
2019	—	`conf`	A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs. ICLR Jack Lindsey, Samuel A. Ocko, Surya Ganguli, Stéphane Deny
2019	J	`jnl`	A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs. CoRR Jack Lindsey, Samuel A. Ocko, Surya Ganguli, Stéphane Deny
2019	A*	`conf`	A unified theory for the origin of grid cells through the lens of pattern formation. NeurIPS Ben Sorscher, Gabriel Mel, Surya Ganguli, Samuel A. Ocko
2019	—	`conf`	An analytic theory of generalization dynamics and transfer learning in deep linear networks. ICLR (Poster) Andrew K. Lampinen, Surya Ganguli
2019	J	`jnl`	Emergent properties of the local geometry of neural loss landscapes. CoRR Stanislav Fort, Surya Ganguli
2019	J	`jnl`	Fast Convolutive Nonnegative Matrix Factorization Through Coordinate and Block Coordinate Updates. CoRR Anthony Degleris, Ben Antin, Surya Ganguli, Alex H. Williams
2019	A*	`conf`	From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction. NeurIPS Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen Baccus, Surya Ganguli
2019	J	`jnl`	From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction. CoRR Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen A. Baccus, Surya Ganguli
2019	A*	`conf`	Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. NeurIPS Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2019	J	`jnl`	Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. CoRR Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2019	A*	`conf`	Universality and individuality in neural dynamics across large populations of recurrent networks. NeurIPS Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2019	J	`jnl`	Universality and individuality in neural dynamics across large populations of recurrent networks. CoRR Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2018	J	`jnl`	A mathematical theory of semantic development in deep neural networks. CoRR Andrew M. Saxe, James L. McClelland, Surya Ganguli
2018	J	`jnl`	An analytic theory of generalization dynamics and transfer learning in deep linear networks. CoRR Andrew K. Lampinen, Surya Ganguli
2018	J	`jnl`	Inferring hidden structure in multilayered neural circuits. PLoS Comput. Biol. Niru Maheswaranathan, David B. Kastner, Stephen A. Baccus, Surya Ganguli
2018	A*	`conf`	Statistical mechanics of low-rank tensor decomposition. NeurIPS Jonathan Kadmon, Surya Ganguli
2018	J	`jnl`	Statistical mechanics of low-rank tensor decomposition. CoRR Jonathan Kadmon, Surya Ganguli
2018	J	`jnl`	SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks. Neural Comput. Friedemann Zenke, Surya Ganguli
2018	A*	`conf`	Task-Driven Convolutional Recurrent Models of the Visual System. NeurIPS Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2018	J	`jnl`	Task-Driven Convolutional Recurrent Models of the Visual System. CoRR Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2018	J	`jnl`	The Emergence of Spectral Universality in Deep Networks. CoRR Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli
2018	A*	`conf`	The emergence of multiple retinal cell types through efficient coding of natural movies. NeurIPS Samuel A. Ocko, Jack Lindsey, Surya Ganguli, Stéphane Deny
2018	A	`conf`	The emergence of spectral universality in deep networks. AISTATS Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli
2017	J	`jnl`	Biologically inspired protection of deep networks from adversarial attacks. CoRR Aran Nayebi, Surya Ganguli
2017	A*	`conf`	Continual Learning Through Synaptic Intelligence. ICML Friedemann Zenke, Ben Poole, Surya Ganguli
2017	—	`conf`	Deep Information Propagation. ICLR (Poster) Samuel S. Schoenholz, Justin Gilmer, Surya Ganguli, Jascha Sohl-Dickstein
2017	J	`jnl`	Improved multitask learning through synaptic intelligence. CoRR Friedemann Zenke, Ben Poole, Surya Ganguli
2017	—	`conf`	Intelligent synapses for multi-task and transfer learning. ICLR (Workshop) Ben Poole, Friedemann Zenke, Surya Ganguli
2017	A*	`conf`	On the Expressive Power of Deep Neural Networks. ICML Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein
2017	J	`jnl`	Pyret: A Python package for analysis of neurophysiology data. J. Open Source Softw. Benjamin Naecker, Niru Maheswaranathan, Surya Ganguli, Stephen Baccus
2017	—	`conf`	Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice. NIPS Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli
2017	J	`jnl`	Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice. CoRR Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli
2017	J	`jnl`	SuperSpike: Supervised learning in multi-layer spiking neural networks. CoRR Friedemann Zenke, Surya Ganguli
2017	—	`conf`	Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net. NIPS Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio
2017	J	`jnl`	Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net. CoRR Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio
2016	J	`jnl`	A universal tradeoff between power, precision and speed in physical communication. CoRR Subhaneil Lahiri, Jascha Sohl-Dickstein, Surya Ganguli
2016	—	`conf`	An equivalence between high dimensional Bayes optimal inference and M-estimation. NIPS Madhu Advani, Surya Ganguli
2016	J	`jnl`	Deep Information Propagation. CoRR Samuel S. Schoenholz, Justin Gilmer, Surya Ganguli, Jascha Sohl-Dickstein
2016	—	`conf`	Deep Learning Models of the Retinal Response to Natural Scenes. NIPS Lane McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen Baccus
2016	—	`conf`	Exponential expressivity in deep neural networks through transient chaos. NIPS Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli
2016	J	`jnl`	Exponential expressivity in deep neural networks through transient chaos. CoRR Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli
2016	J	`jnl`	On the expressive power of deep neural networks. CoRR Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein
2016	J	`jnl`	Random projections of random manifolds. CoRR Subhaneil Lahiri, Peiran Gao, Surya Ganguli
2016	J	`jnl`	Survey of Expressivity in Deep Neural Networks. CoRR Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein
2015	—	`conf`	Deep Knowledge Tracing. NIPS Chris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, Jascha Sohl-Dickstein
2015	J	`jnl`	Deep Knowledge Tracing. CoRR Chris Piech, Jonathan Spencer, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, Jascha Sohl-Dickstein
2015	A*	`conf`	Deep Unsupervised Learning using Nonequilibrium Thermodynamics. ICML Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli
2015	J	`jnl`	Deep Unsupervised Learning using Nonequilibrium Thermodynamics. CoRR Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli
2015	J	`jnl`	Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences. Frontiers Comput. Neurosci. Kristofer E. Bouchard, Surya Ganguli, Michael S. Brainard
2014	J	`jnl`	Analyzing noise in autoencoders and deep networks. CoRR Ben Poole, Jascha Sohl-Dickstein, Surya Ganguli
2014	—	`conf`	Exact solutions to the nonlinear dynamics of learning in deep linear neural networks. ICLR Andrew M. Saxe, James L. McClelland, Surya Ganguli
2014	A*	`conf`	Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods. ICML Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli
2014	—	`conf`	Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. NIPS Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio
2014	J	`jnl`	Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. CoRR Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio
2014	J	`jnl`	On the saddle point problem for non-convex optimization. CoRR Razvan Pascanu, Yann N. Dauphin, Surya Ganguli, Yoshua Bengio
2013	—	`conf`	A memory frontier for complex synapses. NIPS Subhaneil Lahiri, Surya Ganguli
2013	J	`jnl`	An adaptive low dimensional quasi-Newton sum of functions optimizer. CoRR Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli
2013	—	`conf`	Investigating the role of firing-rate normalization and dimensionality reduction in brain-machine interface robustness. EMBC Jonathan C. Kao, Paul Nuyujukian, Sergey D. Stavisky, Stephen I. Ryu, Surya Ganguli, Krishna V. Shenoy
2013	B	`conf`	Learning hierarchical categories in deep neural networks. CogSci Andrew M. Saxe, James L. McClelland, Surya Ganguli
2010	—	`conf`	Short-term memory in neuronal networks through dynamical compressed sensing. NIPS Surya Ganguli, Haim Sompolinsky