More from the Same Authors

• 2021 : Learning the solar latent space: sigma-variational autoencoders for multiple channel solar imaging »
  Edward Brown · Christopher Bridges · Bernard Benson · Atilim Gunes Baydin
• 2021 : Simultaneous Multivariate Forecast of Space Weather Indices using Deep Neural Network Ensembles »
  Bernard Benson · Christopher Bridges · Atilim Gunes Baydin
• 2021 : Dropout and Ensemble Networks for Thermospheric Density Uncertainty Estimation »
  Stefano Bonasera · Giacomo Acciarini · Jorge Pérez-Hernández · Bernard Benson · Edward Brown · Eric Sutton · Moriba Jah · Christopher Bridges · Atilim Gunes Baydin
• 2022 : Unmasking the Lottery Ticket Hypothesis: Efficient Adaptive Pruning for Finding Winning Tickets »
  Mansheej Paul · Feng Chen · Brett Larsen · Jonathan Frankle · Surya Ganguli · Gintare Karolina Dziugaite
• 2022 : Inferring molecular complexity from mass spectrometry data using machine learning »
  Timothy Gebhard · Aaron C. Bell · Jian Gong · Jaden J. A. Hastings · George Fricke · Nathalie Cabrol · Scott Sandford · Michael Phillips · Kimberley Warren-Rhodes · Atilim Gunes Baydin
• 2023 Poster: Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks »
  Feng Chen · Daniel Kunin · Atsushi Yamamura · Surya Ganguli
• 2023 Poster: Information Geometry of the Retinal Representation Manifold »
  Xuehao Ding · Dongsoo Lee · Joshua Melander · George Sivulka · Surya Ganguli · Stephen Baccus
• 2023 Poster: Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression »
  Allan Raventós · Mansheej Paul · Feng Chen · Surya Ganguli
• 2023 Workshop: NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences »
  Brian Nord · Atilim Gunes Baydin · Adji Bousso Dieng · Emine Kucukbenli · Siddharth Mishra-Sharma · Benjamin Nachman · Kyle Cranmer · Gilles Louppe · Savannah Thais
• 2022 Workshop: Machine Learning and the Physical Sciences »
  Atilim Gunes Baydin · Adji Bousso Dieng · Emine Kucukbenli · Gilles Louppe · Siddharth Mishra-Sharma · Benjamin Nachman · Brian Nord · Savannah Thais · Anima Anandkumar · Kyle Cranmer · Lenka Zdeborová · Rianne van den Berg
• 2022 Poster: Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks »
  Mansheej Paul · Brett Larsen · Surya Ganguli · Jonathan Frankle · Gintare Karolina Dziugaite
• 2022 Poster: Beyond neural scaling laws: beating power law scaling via data pruning »
  Ben Sorscher · Robert Geirhos · Shashank Shekhar · Surya Ganguli · Ari Morcos
• 2021 : Session 3 | Contributed talk: Maximilian Dax, "Amortized Bayesian inference of gravitational waves with normalizing flows" »
  Maximilian Dax · Atilim Gunes Baydin
• 2021 : Session 3 | Invited talk: Laure Zanna, "The future of climate modeling in the age of machine learning" »
  Laure Zanna · Atilim Gunes Baydin
• 2021 : Session 2 | Contributed talk: George Stein, "Self-supervised similarity search for large scientific datasets" »
  George Stein · Atilim Gunes Baydin
• 2021 : Session 2 | Invited talk: Megan Ansdell, "NASA's efforts & opportunities to support ML in the Physical Sciences" »
  Megan Ansdell · Atilim Gunes Baydin
• 2021 : Session 1 | Contributed talk: Tian Xie, "Crystal Diffusion Variational Autoencoder for Periodic Material Generation" »
  Tian Xie · Atilim Gunes Baydin
• 2021 : Session 1 | Invited talk: Bingqing Cheng, "Predicting material properties with the help of machine learning" »
  Bingqing Cheng · Atilim Gunes Baydin
• 2021 : Session 1 | Invited talk: Max Welling, "Accelerating simulations of nature, both classical and quantum, with equivariant deep learning" »
  Max Welling · Atilim Gunes Baydin
• 2021 Workshop: Machine Learning and the Physical Sciences »
  Anima Anandkumar · Kyle Cranmer · Mr. Prabhat · Lenka Zdeborová · Atilim Gunes Baydin · Juan Carrasquilla · Emine Kucukbenli · Gilles Louppe · Benjamin Nachman · Brian Nord · Savannah Thais
• 2021 Poster: Deep Learning on a Data Diet: Finding Important Examples Early in Training »
  Mansheej Paul · Surya Ganguli · Gintare Karolina Dziugaite
• 2021 Poster: Domain Invariant Representation Learning with Domain Density Transformations »
  A. Tuan Nguyen · Toan Tran · Yarin Gal · Atilim Gunes Baydin
• 2020 : Session 3 | Invited talk: Laura Waller, "Physics-based Learning for Computational Microscopy" »
  Laura Waller · Atilim Gunes Baydin
• 2020 : Session 2 | Invited talk: Phiala Shanahan, "Generative Flow Models for Gauge Field Theory" »
  Phiala Shanahan · Atilim Gunes Baydin
• 2020 : Session 2 | Invited talk: Estelle Inack, "Variational Neural Annealing" »
  Estelle Inack · Atilim Gunes Baydin
• 2020 : Session 1 | Invited talk: Michael Bronstein, "Geometric Deep Learning for Functional Protein Design" »
  Michael Bronstein · Atilim Gunes Baydin
• 2020 : Session 1 | Invited talk: Lauren Anderson, "3D Milky Way Dust Map using a Scalable Gaussian Process" »
  Lauren Anderson · Atilim Gunes Baydin
• 2020 Workshop: Machine Learning and the Physical Sciences »
  Anima Anandkumar · Kyle Cranmer · Shirley Ho · Mr. Prabhat · Lenka Zdeborová · Atilim Gunes Baydin · Juan Carrasquilla · Adji Bousso Dieng · Karthik Kashinath · Gilles Louppe · Brian Nord · Michela Paganini · Savannah Thais
• 2020 Poster: Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel »
  Stanislav Fort · Gintare Karolina Dziugaite · Mansheej Paul · Sepideh Kharaghani · Daniel Roy · Surya Ganguli
• 2020 Poster: Predictive coding in balanced neural networks with noise, chaos and delays »
  Jonathan Kadmon · Jonathan Timcheck · Surya Ganguli
• 2020 Poster: Identifying Learning Rules From Neural Network Observables »
  Aran Nayebi · Sanjana Srivastava · Surya Ganguli · Daniel Yamins
• 2020 Spotlight: Identifying Learning Rules From Neural Network Observables »
  Aran Nayebi · Sanjana Srivastava · Surya Ganguli · Daniel Yamins
• 2020 Poster: Black-Box Optimization with Local Generative Surrogates »
  Sergey Shirobokov · Vladislav Belavin · Michael Kagan · Andrei Ustyuzhanin · Atilim Gunes Baydin
• 2020 Poster: Pruning neural networks without any data by iteratively conserving synaptic flow »
  Hidenori Tanaka · Daniel Kunin · Daniel Yamins · Surya Ganguli
• 2019 : Panel Session: A new hope for neuroscience »
  Yoshua Bengio · Blake Richards · Timothy Lillicrap · Ila Fiete · David Sussillo · Doina Precup · Konrad Kording · Surya Ganguli
• 2019 : Poster Session »
  Pravish Sainath · Mohamed Akrout · Charles Delahunt · Nathan Kutz · Guangyu Robert Yang · Joseph Marino · L F Abbott · Nicolas Vecoven · Damien Ernst · andrew warrington · Michael Kagan · Kyunghyun Cho · Kameron Harris · Leopold Grinberg · John J. Hopfield · Dmitry Krotov · Taliah Muhammad · Erick Cobos · Edgar Walker · Jacob Reimer · Andreas Tolias · Alexander Ecker · Janaki Sheth · Yu Zhang · Maciej Wołczyk · Jacek Tabor · Szymon Maszke · Roman Pogodin · Dane Corneil · Wulfram Gerstner · Baihan Lin · Guillermo Cecchi · Jenna M Reinen · Irina Rish · Guillaume Bellec · Darjan Salaj · Anand Subramoney · Wolfgang Maass · Yueqi Wang · Ari Pakman · Jin Hyung Lee · Liam Paninski · Bryan Tripp · Colin Graber · Alex Schwing · Luke Prince · Gabriel Ocker · Michael Buice · Benjamin Lansdell · Konrad Kording · Jack Lindsey · Terrence Sejnowski · Matthew Farrell · Eric Shea-Brown · Nicolas Farrugia · Victor Nepveu · Jiwoong Im · Kristin Branson · Brian Hu · Ramakrishnan Iyer · Stefan Mihalas · Sneha Aenugu · Hananel Hazan · Sihui Dai · Tan Nguyen · Doris Tsao · Richard Baraniuk · Anima Anandkumar · Hidenori Tanaka · Aran Nayebi · Stephen Baccus · Surya Ganguli · Dean Pospisil · Eilif Muller · Jeffrey S Cheng · Gaël Varoquaux · Kamalaker Dadi · Dimitrios C Gklezakos · Rajesh PN Rao · Anand Louis · Christos Papadimitriou · Santosh Vempala · Naganand Yadati · Daniel Zdeblick · Daniela M Witten · Nicholas Roberts · Vinay Prabhu · Pierre Bellec · Poornima Ramesh · Jakob H Macke · Santiago Cadena · Guillaume Bellec · Franz Scherr · Owen Marschall · Robert Kim · Hannes Rapp · Marcio Fonseca · Oliver Armitage · Jiwoong Im · Thomas Hardcastle · Abhishek Sharma · Wyeth Bair · Adrian Valente · Shane Shang · Merav Stern · Rutuja Patil · Peter Wang · Sruthi Gorantla · Peter Stratton · Tristan Edwards · Jialin Lu · Martin Ester · Yurii Vlasov · Siavash Golkar
• 2019 : Panel - The Role of Communication at Large: Aparna Lakshmiratan, Jason Yosinski, Been Kim, Surya Ganguli, Finale Doshi-Velez »
  Aparna Lakshmiratan · Finale Doshi-Velez · Surya Ganguli · Zachary Lipton · Michela Paganini · Anima Anandkumar · Jason Yosinski
• 2019 : Invited Talk: Theories for the emergence of internal representations in neural networks: from perception to navigation »
  Surya Ganguli
• 2019 : Surya Ganguli, Yasaman Bahri, Florent Krzakala moderated by Lenka Zdeborova »
  Florent Krzakala · Yasaman Bahri · Surya Ganguli · Lenka Zdeborová · Adji Bousso Dieng · Joan Bruna
• 2019 : Surya Ganguli - An analytic theory of generalization dynamics and transfer learning in deep linear networks »
  Surya Ganguli
• 2019 : Opening Remarks »
  Atilim Gunes Baydin · Juan Carrasquilla · Shirley Ho · Karthik Kashinath · Michela Paganini · Savannah Thais · Anima Anandkumar · Kyle Cranmer · Roger Melko · Mr. Prabhat · Frank Wood
• 2019 Workshop: Machine Learning and the Physical Sciences »
  Atilim Gunes Baydin · Juan Carrasquilla · Shirley Ho · Karthik Kashinath · Michela Paganini · Savannah Thais · Anima Anandkumar · Kyle Cranmer · Roger Melko · Mr. Prabhat · Frank Wood
• 2019 Workshop: Program Transformations for ML »
  Pascal Lamblin · Atilim Gunes Baydin · Alexander Wiltschko · Bart van Merriënboer · Emily Fertig · Barak Pearlmutter · David Duvenaud · Laurent Hascoet
• 2019 Poster: A unified theory for the origin of grid cells through the lens of pattern formation »
  Ben Sorscher · Gabriel Mel · Surya Ganguli · Samuel Ocko
• 2019 Poster: Universality and individuality in neural dynamics across large populations of recurrent networks »
  Niru Maheswaranathan · Alex Williams · Matthew Golub · Surya Ganguli · David Sussillo
• 2019 Spotlight: A unified theory for the origin of grid cells through the lens of pattern formation »
  Ben Sorscher · Gabriel Mel · Surya Ganguli · Samuel Ocko
• 2019 Spotlight: Universality and individuality in neural dynamics across large populations of recurrent networks »
  Niru Maheswaranathan · Alex Williams · Matthew Golub · Surya Ganguli · David Sussillo
• 2019 Poster: From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction »
  Hidenori Tanaka · Aran Nayebi · Niru Maheswaranathan · Lane McIntosh · Stephen Baccus · Surya Ganguli
• 2019 Poster: Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model »
  Atilim Gunes Baydin · Lei Shao · Wahid Bhimji · Lukas Heinrich · Saeid Naderiparizi · Andreas Munk · Jialin Liu · Bradley Gram-Hansen · Gilles Louppe · Lawrence Meadows · Philip Torr · Victor Lee · Kyle Cranmer · Mr. Prabhat · Frank Wood
• 2019 Poster: Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics »
  Niru Maheswaranathan · Alex Williams · Matthew Golub · Surya Ganguli · David Sussillo
• 2018 Poster: The emergence of multiple retinal cell types through efficient coding of natural movies »
  Samuel Ocko · Jack Lindsey · Surya Ganguli · Stephane Deny
• 2018 Poster: Statistical mechanics of low-rank tensor decomposition »
  Jonathan Kadmon · Surya Ganguli
• 2018 Poster: Task-Driven Convolutional Recurrent Models of the Visual System »
  Aran Nayebi · Daniel Bear · Jonas Kubilius · Kohitij Kar · Surya Ganguli · David Sussillo · James J DiCarlo · Daniel Yamins
• 2017 : Panel discussion »
  Atilim Gunes Baydin · Adam Paszke · Jonathan Hüser · Jean Utke · Laurent Hascoet · Jeffrey Siskind · Jan Hueckelheim · Andreas Griewank
• 2017 : Beyond backprop: automatic differentiation in machine learning »
  Atilim Gunes Baydin
• 2017 Workshop: Deep Learning for Physical Sciences »
  Atilim Gunes Baydin · Mr. Prabhat · Kyle Cranmer · Frank Wood
• 2017 Poster: Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net »
  Anirudh Goyal · Nan Rosemary Ke · Surya Ganguli · Yoshua Bengio
• 2017 Poster: Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice »
  Jeffrey Pennington · Samuel Schoenholz · Surya Ganguli
• 2016 : Surya Ganguli : Deep Neural Models of the Retinal Response to Natural Stimuli »
  Surya Ganguli
• 2016 : Non-convexity in the error landscape and the expressive capacity of deep neural networks »
  Surya Ganguli
• 2016 Poster: Exponential expressivity in deep neural networks through transient chaos »
  Ben Poole · Subhaneil Lahiri · Maithra Raghu · Jascha Sohl-Dickstein · Surya Ganguli
• 2016 Poster: An equivalence between high dimensional Bayes optimal inference and M-estimation »
  Madhu Advani · Surya Ganguli
• 2016 Poster: Deep Learning Models of the Retinal Response to Natural Scenes »
  Lane McIntosh · Niru Maheswaranathan · Aran Nayebi · Surya Ganguli · Stephen Baccus
• 2015 Poster: Deep Knowledge Tracing »
  Chris Piech · Jonathan Bassen · Jonathan Huang · Surya Ganguli · Mehran Sahami · Leonidas Guibas · Jascha Sohl-Dickstein
• 2014 Workshop: Deep Learning and Representation Learning »
  Andrew Y Ng · Yoshua Bengio · Adam Coates · Roland Memisevic · Sharanyan Chetlur · Geoffrey E Hinton · Shamim Nemati · Bryan Catanzaro · Surya Ganguli · Herbert Jaeger · Phil Blunsom · Leon Bottou · Volodymyr Mnih · Chen-Yu Lee · Rich M Schwartz
• 2014 Poster: Identifying and attacking the saddle point problem in high-dimensional non-convex optimization »
  Yann N Dauphin · Razvan Pascanu · Caglar Gulcehre · Kyunghyun Cho · Surya Ganguli · Yoshua Bengio
• 2013 Poster: A memory frontier for complex synapses »
  Subhaneil Lahiri · Surya Ganguli
• 2013 Oral: A memory frontier for complex synapses »
  Subhaneil Lahiri · Surya Ganguli
• 2010 Poster: Short-term memory in neuronal networks through dynamical compressed sensing »
  Surya Ganguli · Haim Sompolinsky