Timezone: »
The brain modifies its synaptic strengths during learning in order to better adapt to its environment. However, the underlying plasticity rules that govern learning are unknown. Many proposals have been suggested, including Hebbian mechanisms, explicit error backpropagation, and a variety of alternatives. It is an open question as to what specific experimental measurements would need to be made to determine whether any given learning rule is operative in a real biological system. In this work, we take a "virtual experimental" approach to this problem. Simulating idealized neuroscience experiments with artificial neural networks, we generate a large-scale dataset of learning trajectories of aggregate statistics measured in a variety of neural network architectures, loss functions, learning rule hyperparameters, and parameter initializations. We then take a discriminative approach, training linear and simple non-linear classifiers to identify learning rules from features based on these observables. We show that different classes of learning rules can be separated solely on the basis of aggregate statistics of the weights, activations, or instantaneous layer-wise activity changes, and that these results generalize to limited access to the trajectory and held-out architectures and learning curricula. We identify the statistics of each observable that are most relevant for rule identification, finding that statistics from network activities across training are more robust to unit undersampling and measurement noise than those obtained from the synaptic strengths. Our results suggest that activation patterns, available from electrophysiological recordings of post-synaptic activities on the order of several hundred units, frequently measured at wider intervals over the course of learning, may provide a good basis on which to identify learning rules.
Author Information
Aran Nayebi (Stanford University)
Sanjana Srivastava (Stanford University)
Surya Ganguli (Stanford)
Daniel Yamins (Stanford University)
Related Events (a corresponding poster, oral, or spotlight)
-
2020 Spotlight: Identifying Learning Rules From Neural Network Observables »
Thu. Dec 10th 03:10 -- 03:20 PM Room Orals & Spotlights: Neuroscience
More from the Same Authors
-
2021 Spotlight: Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks »
Aran Nayebi · Alexander Attinger · Malcolm Campbell · Kiah Hardcastle · Isabel Low · Caitlin S Mallory · Gabriel Mel · Ben Sorscher · Alex H Williams · Surya Ganguli · Lisa Giocomo · Dan Yamins -
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 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 | Invited talk: Surya Ganguli, "From the geometry of high dimensional energy landscapes to optimal annealing in a dissipative many body quantum optimizer" »
Surya Ganguli · Atilim Gunes Baydin -
2021 Poster: Deep Learning on a Data Diet: Finding Important Examples Early in Training »
Mansheej Paul · Surya Ganguli · Gintare Karolina Dziugaite -
2021 Poster: Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks »
Aran Nayebi · Alexander Attinger · Malcolm Campbell · Kiah Hardcastle · Isabel Low · Caitlin S Mallory · Gabriel Mel · Ben Sorscher · Alex H Williams · Surya Ganguli · Lisa Giocomo · Dan Yamins -
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: Learning Physical Graph Representations from Visual Scenes »
Daniel Bear · Chaofei Fan · Damian Mrowca · Yunzhu Li · Seth Alter · Aran Nayebi · Jeremy Schwartz · Li Fei-Fei · Jiajun Wu · Josh Tenenbaum · Daniel Yamins -
2020 Poster: Pruning neural networks without any data by iteratively conserving synaptic flow »
Hidenori Tanaka · Daniel Kunin · Daniel Yamins · Surya Ganguli -
2020 Oral: Learning Physical Graph Representations from Visual Scenes »
Daniel Bear · Chaofei Fan · Damian Mrowca · Yunzhu Li · Seth Alter · Aran Nayebi · Jeremy Schwartz · Li Fei-Fei · Jiajun Wu · Josh Tenenbaum · Daniel Yamins -
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 Poster: Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs »
Jonas Kubilius · Martin Schrimpf · Kohitij Kar · Rishi Rajalingham · Ha Hong · Najib Majaj · Elias Issa · Pouya Bashivan · Jonathan Prescott-Roy · Kailyn Schmidt · Aran Nayebi · Daniel Bear · Daniel Yamins · James J DiCarlo -
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 Oral: Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs »
Jonas Kubilius · Martin Schrimpf · Ha Hong · Najib Majaj · Rishi Rajalingham · Elias Issa · Kohitij Kar · Pouya Bashivan · Jonathan Prescott-Roy · Kailyn Schmidt · Aran Nayebi · Daniel Bear · Daniel Yamins · James J DiCarlo -
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: Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics »
Niru Maheswaranathan · Alex Williams · Matthew Golub · Surya Ganguli · David Sussillo -
2018 : Talk 6: Dan Yamins - The Objects of Our Curiosity: Intrinsic Motivation, Intuitive Physics and Self-Supervised Learning »
Daniel Yamins -
2018 Poster: Learning to Play With Intrinsically-Motivated, Self-Aware Agents »
Nick Haber · Damian Mrowca · Stephanie Wang · Li Fei-Fei · Daniel Yamins -
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 -
2018 Poster: Flexible neural representation for physics prediction »
Damian Mrowca · Chengxu Zhuang · Elias Wang · Nick Haber · Li Fei-Fei · Josh Tenenbaum · Daniel Yamins -
2017 Oral: Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System »
Chengxu Zhuang · Jonas Kubilius · Mitra JZ Hartmann · Daniel Yamins -
2017 Poster: Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System »
Chengxu Zhuang · Jonas Kubilius · Mitra JZ Hartmann · Daniel Yamins -
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 -
2013 Poster: Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream »
Daniel L Yamins · Ha Hong · Charles Cadieu · James J DiCarlo -
2010 Poster: Short-term memory in neuronal networks through dynamical compressed sensing »
Surya Ganguli · Haim Sompolinsky