Lucas, James

19 publications

JMLR 2025 Optimizing Data Collection for Machine Learning Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc T. Law

ICLR 2024 Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas

ECCVW 2024 Improving Hyperparameter Optimization with Checkpointed Model Weights Nikhil Mehta, Jonathan Lorraine, Steve Masson, Ramanathan Arunachalam, Zaid Pervaiz Bhat, James Lucas, Arun George Zachariah

ICLR 2024 Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets Yuan-Hong Liao, David Acuna, Rafid Mahmood, James Lucas, Viraj Uday Prabhu, Sanja Fidler

ICCV 2023 ATT3D: Amortized Text-to-3D Object Synthesis Jonathan Lorraine, Kevin Xie, Xiaohui Zeng, Chen-Hsuan Lin, Towaki Takikawa, Nicholas Sharp, Tsung-Yi Lin, Ming-Yu Liu, Sanja Fidler, James Lucas

TMLR 2023 Bridging the Sim2Real Gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting Viraj Uday Prabhu, David Acuna, Rafid Mahmood, Marc T. Law, Yuan-Hong Liao, Judy Hoffman, Sanja Fidler, James Lucas

ICLR 2023 Spacetime Representation Learning Marc T. Law, James Lucas

CVPR 2022 How Much More Data Do I Need? Estimating Requirements for Downstream Tasks Rafid Mahmood, James Lucas, David Acuna, Daiqing Li, Jonah Philion, Jose M. Alvarez, Zhiding Yu, Sanja Fidler, Marc T. Law

NeurIPS 2022 Optimizing Data Collection for Machine Learning Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc Law

ICCVW 2021 Causal BERT: Improving Object Detection by Searching for Challenging Groups Cinjon Resnick, Or Litany, Amlan Kar, Karsten Kreis, James Lucas, Kyunghyun Cho, Sanja Fidler

ICLR 2021 Theoretical Bounds on Estimation Error for Meta-Learning James Lucas, Mengye Ren, Irene Raissa KAMENI Kameni, Toniann Pitassi, Richard Zemel

NeurIPS 2020 Regularized Linear Autoencoders Recover the Principal Components, Eventually Xuchan Bao, James Lucas, Sushant Sachdeva, Roger B Grosse

ICLR 2019 Aggregated Momentum: Stability Through Passive Damping James Lucas, Shengyang Sun, Richard Zemel, Roger Grosse

NeurIPS 2019 Don't Blame the ELBO! a Linear VAE Perspective on Posterior Collapse James Lucas, George Tucker, Roger B Grosse, Mohammad Norouzi

NeurIPS 2019 Lookahead Optimizer: K Steps Forward, 1 Step Back Michael Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton

NeurIPS 2019 Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li, Saminul Haque, Cem Anil, James Lucas, Roger B Grosse, Joern-Henrik Jacobsen

ICML 2019 Sorting Out Lipschitz Function Approximation Cem Anil, James Lucas, Roger Grosse

ICLRW 2019 Understanding Posterior Collapse in Generative Latent Variable Models James Lucas, George Tucker, Roger Grosse, Mohammad Norouzi

ICML 2018 Adversarial Distillation of Bayesian Neural Network Posteriors Kuan-Chieh Wang, Paul Vicol, James Lucas, Li Gu, Roger Grosse, Richard Zemel