James Lucas

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Citations	1235	1233
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Roger GrosseAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Richard ZemelProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
Michael ZhangUniversity of TorontoVerified email at cs.toronto.edu
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
Cem AnilUniversity of Toronto; Vector InstituteVerified email at mail.utoronto.ca
Kuan-Chieh (Jackson) WangStanford UniversityVerified email at stanford.edu
Jimmy BaUniversity of TorontoVerified email at cs.toronto.edu
Mohammad NorouziStartupVerified email at google.com
George TuckerGoogle BrainVerified email at google.com
Mengye RenNYUVerified email at nyu.edu
Sanja FidlerUniversity of Toronto, NVIDIAVerified email at cs.toronto.edu
Jörn-Henrik JacobsenApple AI/ML ResearchVerified email at vectorinstitute.ai
Qiyang LiUniversity of California, BerkeleyVerified email at berkeley.edu
SHENGYANG SUNPhD student, University of TorontoVerified email at cs.toronto.edu
Li GuNoah’s Ark Lab, Huawei CanadaVerified email at huawei.com
Paul VicolUniversity of Toronto & Vector InstituteVerified email at cs.toronto.edu
Eleni TriantafillouGoogle BrainVerified email at google.com
Xaq PitkowAssociate Professor of Computational Neuroscience, Baylor College of Medicine and Rice UniversityVerified email at rice.edu
Jake C. SnellPrinceton UniversityVerified email at princeton.edu
Andreas ToliasDepartment of Neuroscience, Baylor College of MedicineVerified email at cns.bcm.edu

James Lucas

Research Scientist, NVIDIA

Verified email at cs.toronto.edu - Homepage

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Lookahead optimizer: k steps forward, 1 step back M Zhang, J Lucas, J Ba, GE Hinton Advances in neural information processing systems 32, 2019	537	2019
Sorting out Lipschitz function approximation C Anil, J Lucas, R Grosse International Conference on Machine Learning, 291-301, 2019	235	2019
Don't blame the ELBO! A linear VAE perspective on posterior collapse J Lucas, G Tucker, R Grosse, M Norouzi arXiv preprint arXiv:1911.02469, 2019	219*	2019
Preventing gradient attenuation in lipschitz constrained convolutional networks Q Li, S Haque, C Anil, J Lucas, RB Grosse, JH Jacobsen Advances in neural information processing systems 32, 2019	64	2019
Aggregated momentum: Stability through passive damping J Lucas, S Sun, R Zemel, R Grosse arXiv preprint arXiv:1804.00325, 2018	60	2018
Adversarial distillation of bayesian neural network posteriors KC Wang, P Vicol, J Lucas, L Gu, R Grosse, R Zemel International conference on machine learning, 5190-5199, 2018	59	2018
Analyzing monotonic linear interpolation in neural network loss landscapes J Lucas, J Bae, MR Zhang, S Fort, R Zemel, R Grosse arXiv preprint arXiv:2104.11044, 2021	17*	2021
Regularized linear autoencoders recover the principal components, eventually X Bao, J Lucas, S Sachdeva, RB Grosse Advances in Neural Information Processing Systems 33, 6971-6981, 2020	17	2020
Theoretical bounds on estimation error for meta-learning J Lucas, M Ren, I Kameni, T Pitassi, R Zemel arXiv preprint arXiv:2010.07140, 2020	8	2020
Flexible few-shot learning with contextual similarity M Ren, E Triantafillou, KC Wang, J Lucas, J Snell, X Pitkow, AS Tolias, ... arXiv preprint arXiv:2012.05895, 1, 2020	7	2020
Optimizing data collection for machine learning R Mahmood, J Lucas, JM Alvarez, S Fidler, M Law Advances in Neural Information Processing Systems 35, 29915-29928, 2022	3	2022
The Calibration Generalization Gap A Carrell, N Mallinar, J Lucas, P Nakkiran arXiv preprint arXiv:2210.01964, 2022	3	2022
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks R Mahmood, J Lucas, D Acuna, D Li, J Philion, JM Alvarez, Z Yu, S Fidler, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	3	2022
Causal Scene BERT: Improving object detection by searching for challenging groups C Resnick, O Litany, A Kar, K Kreis, J Lucas, K Cho, S Fidler	2*	2022
Few-Shot Attribute Learning M Ren, E Triantafillou, KC Wang, J Lucas, J Snell, X Pitkow, AS Tolias, ...	1	2020
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting V Prabhu, D Acuna, A Liao, R Mahmood, MT Law, J Hoffman, S Fidler, ... arXiv preprint arXiv:2302.04832, 2023		2023
Optimization and loss landscape geometry of deep learning J Lucas University of Toronto (Canada), 2022		2022
Probing Few-Shot Generalization with Attributes M Ren, E Triantafillou, KC Wang, J Lucas, J Snell, X Pitkow, AS Tolias, ... arXiv preprint arXiv:2012.05895, 2020		2020
Spacetime Representation Learning MT Law, J Lucas The Eleventh International Conference on Learning Representations, 0
Exploring representation learning for flexible few-shot tasks M Ren, E Triantafillou, KC Wang, J Lucas, J Snell, X Pitkow, AS Tolias, ...

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