Jascha Sohl-Dickstein

◀ ▶ joint publications with C. Daniel Freeman

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Publications

2023
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  - journals/corr/abs-2311-07587
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  - https://dblp.org/rec/journals/corr/abs-2311-07587
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:
Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? CoRR abs/2311.07587 (2023)
2022
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  - conf/collas/MetzFHMS22
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Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-Dickstein:
Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers. CoLLAs 2022: 142-164
[i72]
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  - journals/corr/abs-2203-11860
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Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-Dickstein:
Practical tradeoffs between memory, compute, and performance in learned optimizers. CoRR abs/2203.11860 (2022)
[i67]
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  - journals/corr/abs-2211-09760
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Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein:
VeLO: Training Versatile Learned Optimizers by Scaling Up. CoRR abs/2211.09760 (2022)
2021
[i65]
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  - journals/corr/abs-2101-07367
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Luke Metz, C. Daniel Freeman, Niru Maheswaranathan, Jascha Sohl-Dickstein:
Training Learned Optimizers with Randomly Initialized Learned Optimizers. CoRR abs/2101.07367 (2021)
2020
[i60]
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  - journals/corr/abs-2002-11887
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Luke Metz, Niru Maheswaranathan, Ruoxi Sun, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein:
Using a thousand optimization tasks to learn hyperparameter search strategies. CoRR abs/2002.11887 (2020)
[i52]
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  - journals/corr/abs-2009-11243
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Luke Metz, Niru Maheswaranathan, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein:
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves. CoRR abs/2009.11243 (2020)
2019
[c33]
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  - conf/icml/MetzMNFS19
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Luke Metz, Niru Maheswaranathan, Jeremy Nixon, C. Daniel Freeman, Jascha Sohl-Dickstein:
Understanding and correcting pathologies in the training of learned optimizers. ICML 2019: 4556-4565
2018
[i29]
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  - journals/corr/abs-1810-10180
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Luke Metz, Niru Maheswaranathan, Jeremy Nixon, C. Daniel Freeman, Jascha Sohl-Dickstein:
Learned optimizers that outperform SGD on wall-clock and test loss. CoRR abs/1810.10180 (2018)

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