C. Daniel Freeman

According to our database, C. Daniel Freeman authored at least 17 papers between 2017 and 2023.

Collaborative distances:

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

2023

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?

C. Daniel Freeman, Laura Culp, Aaron Parisi, Maxwell L. Bileschi, Gamaleldin F. Elsayed, Alex Rizkowsky, Isabelle Simpson, Alex Alemi, Azade Nova, Ben Adlam, Bernd Bohnet, Gaurav Mishra, Hanie Sedghi, Igor Mordatch, Izzeddin Gur, Jaehoon Lee, John D. Co-Reyes, Jeffrey Pennington, Kelvin Xu, Kevin Swersky, Kshiteej Mahajan, Lechao Xiao, Rosanne Liu, Simon Kornblith, Noah Constant, Peter J. Liu, Roman Novak, Yundi Qian, Noah Fiedel, Jascha Sohl-Dickstein

CoRR, 2023

Improving Large Language Model Fine-tuning for Solving Math Problems.

Yixin Liu, Avi Singh, C. Daniel Freeman, John D. Co-Reyes, Peter J. Liu

CoRR, 2023

Allowing Safe Contact in Robotic Goal-Reaching: Planning and Tracking in Operational and Null Spaces.

Xinghao Zhu, Wenzhao Lian, Bodi Yuan, C. Daniel Freeman, Masayoshi Tomizuka

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Transformer-Based Learned Optimization.

Erik Gärtner, Luke Metz, Mykhaylo Andriluka, C. Daniel Freeman, Cristian Sminchisescu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

VeLO: Training Versatile Learned Optimizers by Scaling Up.

Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein

CoRR, 2022

Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning.

Satoshi Kataoka, Seyed Kamyar Seyed Ghasemipour, C. Daniel Freeman, Igor Mordatch

CoRR, 2022

Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers.

Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-Dickstein

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

Gradients are Not All You Need.

Luke Metz, C. Daniel Freeman, Samuel S. Schoenholz, Tal Kachman

CoRR, 2021

Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization.

Shixiang Shane Gu, Manfred Diaz, C. Daniel Freeman, Hiroki Furuta, Seyed Kamyar Seyed Ghasemipour, Anton Raichuk, Byron David, Erik Frey, Erwin Coumans, Olivier Bachem

CoRR, 2021

Training Learned Optimizers with Randomly Initialized Learned Optimizers.

Luke Metz, C. Daniel Freeman, Niru Maheswaranathan, Jascha Sohl-Dickstein

CoRR, 2021

Brax - A Differentiable Physics Engine for Large Scale Rigid Body Simulation.

C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, Olivier Bachem

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves.

Luke Metz, Niru Maheswaranathan, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein

CoRR, 2020

Using a thousand optimization tasks to learn hyperparameter search strategies.

Luke Metz, Niru Maheswaranathan, Ruoxi Sun, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein

CoRR, 2020

2019

Learning to Predict Without Looking Ahead: World Models Without Forward Prediction.

C. Daniel Freeman, David Ha, Luke Metz

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Understanding and correcting pathologies in the training of learned optimizers.

Luke Metz, Niru Maheswaranathan, Jeremy Nixon, C. Daniel Freeman, Jascha Sohl-Dickstein

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Learned optimizers that outperform SGD on wall-clock and test loss.

Luke Metz, Niru Maheswaranathan, Jeremy Nixon, C. Daniel Freeman, Jascha Sohl-Dickstein

CoRR, 2018

2017

Topology and Geometry of Half-Rectified Network Optimization.

C. Daniel Freeman, Joan Bruna

Proceedings of the 5th International Conference on Learning Representations, 2017