


Остановите войну!
for scientists:


default search action
Luke Metz
Person information

Refine list

refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2022
- [c17]Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster:
Lyapunov Exponents for Diversity in Differentiable Games. AAMAS 2022: 842-852 - [c16]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 - [c15]Paul Vicol, Luke Metz, Jascha Sohl-Dickstein:
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies (Extended Abstract). IJCAI 2022: 5354-5358 - [i28]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) - [i27]James Harrison, Luke Metz, Jascha Sohl-Dickstein:
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases. CoRR abs/2209.11208 (2022) - [i26]Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster:
Discovered Policy Optimisation. CoRR abs/2210.05639 (2022) - [i25]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) - [i24]Erik Gärtner, Luke Metz, Mykhaylo Andriluka, C. Daniel Freeman, Cristian Sminchisescu:
Transformer-Based Learned Optimization. CoRR abs/2212.01055 (2022) - [i23]Louis Kirsch, James Harrison, Jascha Sohl-Dickstein, Luke Metz:
General-Purpose In-Context Learning by Meta-Learning Transformers. CoRR abs/2212.04458 (2022) - 2021
- [c14]Amil Merchant, Luke Metz, Samuel S. Schoenholz, Ekin D. Cubuk:
Learn2Hop: Learned Optimization on Rough Landscapes. ICML 2021: 7643-7653 - [c13]Geoffrey Roeder, Luke Metz, Durk Kingma:
On Linear Identifiability of Learned Representations. ICML 2021: 9030-9039 - [c12]Paul Vicol, Luke Metz, Jascha Sohl-Dickstein:
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies. ICML 2021: 10553-10563 - [c11]Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein:
Reverse engineering learned optimizers reveals known and novel mechanisms. NeurIPS 2021: 19910-19922 - [i22]Luke Metz, C. Daniel Freeman, Niru Maheswaranathan, Jascha Sohl-Dickstein:
Training Learned Optimizers with Randomly Initialized Learned Optimizers. CoRR abs/2101.07367 (2021) - [i21]Amil Merchant, Luke Metz, Samuel S. Schoenholz, Ekin Dogus Cubuk:
Learn2Hop: Learned Optimization on Rough Landscapes. CoRR abs/2107.09661 (2021) - [i20]Luke Metz, C. Daniel Freeman, Samuel S. Schoenholz, Tal Kachman:
Gradients are Not All You Need. CoRR abs/2111.05803 (2021) - [i19]Paul Vicol, Luke Metz, Jascha Sohl-Dickstein:
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies. CoRR abs/2112.13835 (2021) - [i18]Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster:
Lyapunov Exponents for Diversity in Differentiable Games. CoRR abs/2112.14570 (2021) - 2020
- [c10]Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alexander Peysakhovich, Aldo Pacchiano, Jakob N. Foerster:
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian. NeurIPS 2020 - [i17]Ishaan Gulrajani, Colin Raffel, Luke Metz:
Towards GAN Benchmarks Which Require Generalization. CoRR abs/2001.03653 (2020) - [i16]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) - [i15]Geoffrey Roeder, Luke Metz, Diederik P. Kingma:
On Linear Identifiability of Learned Representations. CoRR abs/2007.00810 (2020) - [i14]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) - [i13]Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein:
Reverse engineering learned optimizers reveals known and novel mechanisms. CoRR abs/2011.02159 (2020) - [i12]Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alex Peysakhovich, Aldo Pacchiano, Jakob N. Foerster:
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian. CoRR abs/2011.06505 (2020) - [i11]Michael Laskin, Luke Metz, Seth Nabarrao, Mark Saroufim, Badreddine Noune, Carlo Luschi, Jascha Sohl-Dickstein, Pieter Abbeel:
Parallel Training of Deep Networks with Local Updates. CoRR abs/2012.03837 (2020)
2010 – 2019
- 2019
- [c9]Ishaan Gulrajani, Colin Raffel, Luke Metz:
Towards GAN Benchmarks Which Require Generalization. ICLR (Poster) 2019 - [c8]Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein:
Meta-Learning Update Rules for Unsupervised Representation Learning. ICLR 2019 - [c7]Niru Maheswaranathan, Luke Metz, George Tucker, Dami Choi, Jascha Sohl-Dickstein:
Guided evolutionary strategies: augmenting random search with surrogate gradients. ICML 2019: 4264-4273 - [c6]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 - [c5]C. Daniel Freeman, David Ha, Luke Metz:
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction. NeurIPS 2019: 5380-5391 - [i10]Luke Metz, Niru Maheswaranathan, Jonathon Shlens, Jascha Sohl-Dickstein, Ekin D. Cubuk:
Using learned optimizers to make models robust to input noise. CoRR abs/1906.03367 (2019) - [i9]Zhen Xu, Andrew M. Dai, Jonas Kemp, Luke Metz:
Learning an Adaptive Learning Rate Schedule. CoRR abs/1909.09712 (2019) - [i8]C. Daniel Freeman, Luke Metz, David Ha:
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction. CoRR abs/1910.13038 (2019) - 2018
- [c4]Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow:
Adversarial Spheres. ICLR (Workshop) 2018 - [c3]Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein:
Learning to Learn Without Labels. ICLR (Workshop) 2018 - [i7]Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow:
Adversarial Spheres. CoRR abs/1801.02774 (2018) - [i6]Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein:
Learning Unsupervised Learning Rules. CoRR abs/1804.00222 (2018) - [i5]Niru Maheswaranathan, Luke Metz, George Tucker, Jascha Sohl-Dickstein:
Guided evolutionary strategies: escaping the curse of dimensionality in random search. CoRR abs/1806.10230 (2018) - [i4]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) - 2017
- [c2]Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein:
Unrolled Generative Adversarial Networks. ICLR (Poster) 2017 - [i3]David Berthelot, Tom Schumm, Luke Metz:
BEGAN: Boundary Equilibrium Generative Adversarial Networks. CoRR abs/1703.10717 (2017) - [i2]Luke Metz, Julian Ibarz, Navdeep Jaitly, James Davidson:
Discrete Sequential Prediction of Continuous Actions for Deep RL. CoRR abs/1705.05035 (2017) - 2016
- [c1]Alec Radford, Luke Metz, Soumith Chintala:
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. ICLR (Poster) 2016 - [i1]Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein:
Unrolled Generative Adversarial Networks. CoRR abs/1611.02163 (2016)
Coauthor Index

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
load content from web.archive.org
Privacy notice: By enabling the option above, your browser will contact the API of web.archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2023-02-18 22:50 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint