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Author Information
Timothy Lillicrap (Google DeepMind)
James J DiCarlo (Massachusetts Institute of Technology)
Prof. DiCarlo received his Ph.D. in biomedical engineering and his M.D. from Johns Hopkins in 1998, and did his postdoctoral training in primate visual neurophysiology at Baylor College of Medicine. He joined the MIT faculty in 2002. He is a Sloan Fellow, a Pew Scholar, and a McKnight Scholar. His lab’s research goal is a computational understanding of the brain mechanisms that underlie object recognition. They use large-scale neurophysiology, brain imaging, optogenetic methods, and high-throughput computational simulations to understand how the primate ventral visual stream is able to untangle object identity from other latent image variables such as object position, scale, and pose. They have shown that populations of neurons at the highest cortical visual processing stage (IT) rapidly convey explicit representations of object identity, and that this ability is reshaped by natural visual experience. They have also shown how visual recognition tests can be used to discover new, high-performing bio-inspired algorithms. This understanding may inspire new machine vision systems, new neural prosthetics, and a foundation for understanding how high-level visual representation is altered in conditions such as agnosia, autism and dyslexia.
Christopher Rozell (Georgia Institute of Technology)
Viren Jain (Google)
Nathan Kutz (University of Washington)
William Gray Roncal (Johns Hopkins University)
Bingni Brunton (University of Washington)
More from the Same Authors
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2021 : ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation »
Chuang Gan · Jeremy Schwartz · Seth Alter · Damian Mrowca · Martin Schrimpf · James Traer · Julian De Freitas · Jonas Kubilius · Abhishek Bhandwaldar · Nick Haber · Megumi Sano · Kuno Kim · Elias Wang · Michael Lingelbach · Aidan Curtis · Kevin Feigelis · Daniel Bear · Dan Gutfreund · David Cox · Antonio Torralba · James J DiCarlo · Josh Tenenbaum · Josh McDermott · Dan Yamins -
2021 Spotlight: The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning »
Shahab Bakhtiari · Patrick Mineault · Timothy Lillicrap · Christopher Pack · Blake Richards -
2022 : Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics »
Noga Mudrik · Yenho Chen · Eva Yezerets · Christopher Rozell · Adam Charles -
2022 : Measuring the Alignment of ANNs and Primate V1 on Luminance and Contrast Response Characteristics »
Stephanie Olaiya · Tiago Marques · James J DiCarlo -
2022 : Implementing Divisive Normalization in CNNs Improves Robustness to Common Image Corruptions »
Andrew Cirincione · Reginald Verrier · Artiom Bic · Stephanie Olaiya · James J DiCarlo · Lawrence Udeigwe · Tiago Marques -
2022 : Primate Inferotemporal Cortex Neurons Generalize Better to Novel Image Distributions Than Analogous Deep Neural Networks Units »
Marliawaty I Gusti Bagus · Tiago Marques · Sachi Sanghavi · James J DiCarlo · Martin Schrimpf -
2022 : Evaluating Long-Term Memory in 3D Mazes »
Jurgis Pašukonis · Timothy Lillicrap · Danijar Hafner -
2023 : Attention for Causal Relationship Discovery from Biological Neural Dynamics »
Ziyu Lu · Anika Tabassum · Shruti Kulkarni · Lu Mi · Nathan Kutz · Eric Shea-Brown · Seung-Hwan Lim -
2023 Poster: AndroidInTheWild: A Large-Scale Dataset For Android Device Control »
Christopher Rawles · Alice Li · Daniel Rodriguez · Oriana Riva · Timothy Lillicrap -
2023 Poster: Strong and Precise Modulation of Human Percepts via Robustified ANNs »
Guy Gaziv · Michael Lee · James J DiCarlo -
2023 : Deep Generative Modeling for Data-driven Identification of Noisy, Non-stationary Dynamical Systems »
Doris Voina · Nathan Kutz · Steven Brunton -
2022 : A report on recent experimental tests of two predictions of contemporary computable models of the biological deep neural network underling primate visual intelligence »
James J DiCarlo -
2022 : Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings »
Sabera Talukder · Jennifer J Sun · Matthew Leonard · Bingni Brunton · Yisong Yue -
2022 Poster: Large-Scale Retrieval for Reinforcement Learning »
Peter Humphreys · Arthur Guez · Olivier Tieleman · Laurent Sifre · Theophane Weber · Timothy Lillicrap -
2022 Poster: Intra-agent speech permits zero-shot task acquisition »
Chen Yan · Federico Carnevale · Petko I Georgiev · Adam Santoro · Aurelia Guy · Alistair Muldal · Chia-Chun Hung · Joshua Abramson · Timothy Lillicrap · Gregory Wayne -
2022 Poster: On the Stability and Scalability of Node Perturbation Learning »
Naoki Hiratani · Yash Mehta · Timothy Lillicrap · Peter E Latham -
2022 Poster: How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? »
Chengxu Zhuang · Violet Xiang · Yoon Bai · Xiaoxuan Jia · Nicholas Turk-Browne · Kenneth Norman · James J DiCarlo · Dan Yamins -
2021 : Combining Different V1 Brain Model Variants to Improve Robustness to Image Corruptions in CNNs »
Avinash Baidya · Joel Dapello · James J DiCarlo · Tiago Marques -
2021 Poster: The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning »
Shahab Bakhtiari · Patrick Mineault · Timothy Lillicrap · Christopher Pack · Blake Richards -
2021 Poster: Towards Biologically Plausible Convolutional Networks »
Roman Pogodin · Yash Mehta · Timothy Lillicrap · Peter E Latham -
2021 Poster: Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception »
Joel Dapello · Jenelle Feather · Hang Le · Tiago Marques · David Cox · Josh McDermott · James J DiCarlo · Sueyeon Chung -
2021 : ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation »
Chuang Gan · Jeremy Schwartz · Seth Alter · Damian Mrowca · Martin Schrimpf · James Traer · Julian De Freitas · Jonas Kubilius · Abhishek Bhandwaldar · Nick Haber · Megumi Sano · Kuno Kim · Elias Wang · Michael Lingelbach · Aidan Curtis · Kevin Feigelis · Daniel Bear · Dan Gutfreund · David Cox · Antonio Torralba · James J DiCarlo · Josh Tenenbaum · Josh McDermott · Dan Yamins -
2020 Poster: Learning sparse codes from compressed representations with biologically plausible local wiring constraints »
Kion Fallah · Adam A Willats · Ninghao Liu · Christopher Rozell -
2020 Poster: A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network »
Basile Confavreux · Friedemann Zenke · Everton Agnes · Timothy Lillicrap · Tim Vogels -
2020 Spotlight: A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network »
Basile Confavreux · Friedemann Zenke · Everton Agnes · Timothy Lillicrap · Tim Vogels -
2020 Poster: Generative causal explanations of black-box classifiers »
Matthew O'Shaughnessy · Gregory Canal · Marissa Connor · Christopher Rozell · Mark Davenport -
2020 Poster: Training Generative Adversarial Networks by Solving Ordinary Differential Equations »
Chongli Qin · Yan Wu · Jost Tobias Springenberg · Andy Brock · Jeff Donahue · Timothy Lillicrap · Pushmeet Kohli -
2020 Spotlight: Training Generative Adversarial Networks by Solving Ordinary Differential Equations »
Chongli Qin · Yan Wu · Jost Tobias Springenberg · Andy Brock · Jeff Donahue · Timothy Lillicrap · Pushmeet Kohli -
2020 Poster: Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations »
Joel Dapello · Tiago Marques · Martin Schrimpf · Franziska Geiger · David Cox · James J DiCarlo -
2020 Spotlight: Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations »
Joel Dapello · Tiago Marques · Martin Schrimpf · Franziska Geiger · David Cox · James J DiCarlo -
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 : Invited Talk: Deep learning without weight transport »
Timothy Lillicrap -
2019 : Panel Discussion »
Linda Smith · Josh Tenenbaum · Lisa Anne Hendricks · James McClelland · Timothy Lillicrap · Jesse Thomason · Jason Baldridge · Louis-Philippe Morency -
2019 : Timothy Lillicrap »
Timothy Lillicrap -
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: Hierarchical Optimal Transport for Multimodal Distribution Alignment »
John Lee · Max Dabagia · Eva Dyer · Christopher Rozell -
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: Experience Replay for Continual Learning »
David Rolnick · Arun Ahuja · Jonathan Richard Schwarz · Timothy Lillicrap · Gregory Wayne -
2019 Poster: Deep Learning without Weight Transport »
Mohamed Akrout · Collin Wilson · Peter Humphreys · Timothy Lillicrap · Douglas Tweed -
2018 : Invited Talk 2 »
Timothy Lillicrap -
2018 Poster: Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures »
Sergey Bartunov · Adam Santoro · Blake Richards · Luke Marris · Geoffrey E Hinton · Timothy Lillicrap -
2018 Poster: Learning Attractor Dynamics for Generative Memory »
Yan Wu · Gregory Wayne · Karol Gregor · Timothy Lillicrap -
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: Relational recurrent neural networks »
Adam Santoro · Ryan Faulkner · David Raposo · Jack Rae · Mike Chrzanowski · Theophane Weber · Daan Wierstra · Oriol Vinyals · Razvan Pascanu · Timothy Lillicrap -
2017 : Closing Panel: Analyzing brain data from nano to macroscale »
William Gray Roncal · Eva Dyer -
2017 : Scalable RL and AlphaGo »
Timothy Lillicrap -
2017 : Discovery of governing equations and biological principles from spatio-temporal time-series recordings »
Nathan Kutz -
2017 : Multimodal deep learning for natural human neural recordings and video »
Bingni Brunton -
2017 : Algorithms, tools, and progress in connectomic reconstruction of neural circuits »
Viren Jain -
2017 : Backpropagation and deep learning in the brain »
Timothy Lillicrap -
2017 : Can brain data be used to reverse engineer the algorithms of human perception? »
James J DiCarlo -
2017 : Opening Remarks »
Eva Dyer · William Gray Roncal -
2017 Workshop: BigNeuro 2017: Analyzing brain data from nano to macroscale »
Eva Dyer · Gregory Kiar · William Gray Roncal · · Konrad P Koerding · Joshua T Vogelstein -
2017 Poster: A simple neural network module for relational reasoning »
Adam Santoro · David Raposo · David Barrett · Mateusz Malinowski · Razvan Pascanu · Peter Battaglia · Timothy Lillicrap -
2017 Spotlight: A simple neural network module for relational reasoning »
Adam Santoro · David Raposo · David Barrett · Mateusz Malinowski · Razvan Pascanu · Peter Battaglia · Timothy Lillicrap -
2017 Poster: Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning »
Shixiang (Shane) Gu · Timothy Lillicrap · Richard Turner · Zoubin Ghahramani · Bernhard Schölkopf · Sergey Levine -
2016 : Tim Lillicrap »
Timothy Lillicrap -
2016 Workshop: Connectomics II: Opportunities and Challenges for Machine Learning »
Viren Jain · Srinivas C Turaga -
2016 Poster: Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes »
Jack Rae · Jonathan J Hunt · Ivo Danihelka · Tim Harley · Andrew Senior · Gregory Wayne · Alex Graves · Timothy Lillicrap -
2016 Poster: Combinatorial Energy Learning for Image Segmentation »
Jeremy Maitin-Shepard · Viren Jain · Michal Januszewski · Peter Li · Pieter Abbeel -
2016 Poster: Matching Networks for One Shot Learning »
Oriol Vinyals · Charles Blundell · Timothy Lillicrap · koray kavukcuoglu · Daan Wierstra -
2015 : Spotlight »
Furong Huang · William Gray Roncal · Tom Goldstein -
2015 Poster: Learning Continuous Control Policies by Stochastic Value Gradients »
Nicolas Heess · Gregory Wayne · David Silver · Timothy Lillicrap · Tom Erez · Yuval Tassa -
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 -
2013 Tutorial: Mechanisms Underlying Visual Object Recognition: Humans vs. Neurons vs. Machines »
James J DiCarlo -
2008 Poster: Natural Image Denoising with Convolutional Networks »
Viren Jain · H. Sebastian Seung