Lorraine, Jonathan

8 publications

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

NeurIPS 2024 Training Data Attribution via Approximate Unrolling Juhan Bae, Wu Lin, Jonathan Lorraine, Roger Grosse

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

NeurIPSW 2023 Using Large Language Models for Hyperparameter Optimization Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba

NeurIPS 2021 Meta-Learning to Improve Pre-Training Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David K. Duvenaud

AISTATS 2020 Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine, Paul Vicol, David Duvenaud

ICLR 2019 Self-Tuning Networks: Bilevel Optimization of Hyperparameters Using Structured Best-Response Functions Matthew Mackay, Paul Vicol, Jonathan Lorraine, David Duvenaud, Roger Grosse