Jonathan Lorraine

According to our database, Jonathan Lorraine authored at least 15 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

LATTE3D: Large-scale Amortized Text-To-Enhanced3D Synthesis.

Kevin Xie, Jonathan Lorraine, Tianshi Cao, Jun Gao, James Lucas, Antonio Torralba, Sanja Fidler, Xiaohui Zeng

CoRR, 2024

2023

Using Large Language Models for Hyperparameter Optimization.

Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba

CoRR, 2023

Graph Metanetworks for Processing Diverse Neural Architectures.

Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas

CoRR, 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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Task Selection for AutoML System Evaluation.

Jonathan Lorraine, Nihesh Anderson, Chansoo Lee, Quentin de Laroussilhe, Mehadi Hassen

CoRR, 2022

On Implicit Bias in Overparameterized Bilevel Optimization.

Paul Vicol, Jonathan P. Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse

Proceedings of the International Conference on Machine Learning, 2022

Lyapunov Exponents for Diversity in Differentiable Games.

Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Complex Momentum for Optimization in Games.

Jonathan P. Lorraine, David Acuna, Paul Vicol, David Duvenaud

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Input Convex Gradient Networks.

Jack Richter-Powell, Jonathan Lorraine, Brandon Amos

CoRR, 2021

Complex Momentum for Learning in Games.

Jonathan Lorraine, David Acuna, Paul Vicol, David Duvenaud

CoRR, 2021

Meta-learning to Improve Pre-training.

Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Optimizing Millions of Hyperparameters by Implicit Differentiation.

Jonathan Lorraine, Paul Vicol, David Duvenaud

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Understanding Neural Architecture Search Techniques.

George Adam, Jonathan Lorraine

CoRR, 2019

Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions.

Matthew MacKay, Paul Vicol, Jonathan Lorraine, David Duvenaud, Roger B. Grosse

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Stochastic Hyperparameter Optimization through Hypernetworks.

Jonathan Lorraine, David Duvenaud

CoRR, 2018