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ORCIDYutian Chen 0001
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- affiliation: Google DeepMind, London, UK
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- Yutian Chen — disambiguation page
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2020 – today
- 2024
[c29]Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci, Thomas Paine, Yutian Chen, Misha Denil:
π2vec: Policy Representation with Successor Features. ICLR 2024- [c28]Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen:
Position: Leverage Foundational Models for Black-Box Optimization. ICML 2024 - [i31]Konrad Zolna, Serkan Cabi, Yutian Chen, Eric Lau, Claudio Fantacci, Jurgis Pasukonis, Jost Tobias Springenberg, Sergio Gomez Colmenarejo:
GATS: Gather-Attend-Scatter. CoRR abs/2401.08525 (2024) - [i30]Xingyou Song, Oscar Li, Chansoo Lee, Bangding Yang, Daiyi Peng, Sagi Perel, Yutian Chen:
OmniPred: Language Models as Universal Regressors. CoRR abs/2402.14547 (2024) - [i29]Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George-Cristian Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando de Freitas, Caglar Gulcehre
:
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. CoRR abs/2402.19427 (2024) - [i28]Aleksandar Botev, Soham De, Samuel L. Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz GUStavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas:
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. CoRR abs/2404.07839 (2024) - [i27]Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen:
Position: Leverage Foundational Models for Black-Box Optimization. CoRR abs/2405.03547 (2024) - 2023
- [j6]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuan Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. J. Mach. Learn. Res. 24: 308:1-308:77 (2023) - [c27]Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag:
Discovering Evolution Strategies via Meta-Black-Box Optimization. GECCO Companion 2023: 29-30 - [c26]Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag:
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. GECCO 2023: 929-937 - [c25]Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag:
Discovering Evolution Strategies via Meta-Black-Box Optimization. ICLR 2023 - [i26]Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag:
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. CoRR abs/2304.03995 (2023) - [i25]Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci, Tom Le Paine, Yutian Chen, Misha Denil:
π2vec: Policy Representations with Successor Features. CoRR abs/2306.09800 (2023) - 2022
- [j5]Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet:
On Instrumental Variable Regression for Deep Offline Policy Evaluation. J. Mach. Learn. Res. 23: 302:1-302:40 (2022) - [j4]Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas:
A Generalist Agent. Trans. Mach. Learn. Res. 2022 (2022) - [c24]Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen:
Introducing Symmetries to Black Box Meta Reinforcement Learning. AAAI 2022: 7202-7210 - [c23]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS 2022 - [i24]Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas:
A Generalist Agent. CoRR abs/2205.06175 (2022) - [i23]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR abs/2205.13320 (2022) - [i22]Lucio M. Dery, Abram L. Friesen, Nando de Freitas, Marc'Aurelio Ranzato, Yutian Chen:
Multi-step Planning for Automated Hyperparameter Optimization with OptFormer. CoRR abs/2210.04971 (2022) - [i21]Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dallibard, Chris Lu, Satinder Singh, Sebastian Flennerhag:
Discovering Evolution Strategies via Meta-Black-Box Optimization. CoRR abs/2211.11260 (2022) - [i20]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuang Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. CoRR abs/2211.11747 (2022) - 2021
- [c22]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. ICLR 2021 - [c21]Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton:
Learning Deep Features in Instrumental Variable Regression. ICLR 2021 - [c20]Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas:
Active Offline Policy Selection. NeurIPS 2021: 24631-24644 - [i19]Çaglar Gülçehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew W. Hoffman, Razvan Pascanu, Nando de Freitas:
Regularized Behavior Value Estimation. CoRR abs/2103.09575 (2021) - [i18]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. CoRR abs/2103.16596 (2021) - [i17]Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet:
On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR abs/2105.10148 (2021) - [i16]Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas:
Active Offline Policy Selection. CoRR abs/2106.10251 (2021) - [i15]Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen:
Introducing Symmetries to Black Box Meta Reinforcement Learning. CoRR abs/2109.10781 (2021) - [i14]Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg:
Shaking the foundations: delusions in sequence models for interaction and control. CoRR abs/2110.10819 (2021) - 2020
- [c19]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas:
Modular Meta-Learning with Shrinkage. NeurIPS 2020 - [i13]Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton:
Learning Deep Features in Instrumental Variable Regression. CoRR abs/2010.07154 (2020) - [i12]Yi Yang, Brendan Shillingford, Yannis M. Assael, Miaosen Wang, Wendi Liu, Yutian Chen, Yu Zhang, Eren Sezener, Luis C. Cobo, Misha Denil, Yusuf Aytar, Nando de Freitas:
Large-scale multilingual audio visual dubbing. CoRR abs/2011.03530 (2020)
2010 – 2019
- 2019
- [c18]Yutian Chen, Yannis M. Assael, Brendan Shillingford, David Budden, Scott E. Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Çaglar Gülçehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas:
Sample Efficient Adaptive Text-to-Speech. ICLR (Poster) 2019 - [i11]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas:
Modular Meta-Learning with Shrinkage. CoRR abs/1909.05557 (2019) - 2018
- [c17]Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo J. Rezende, Oriol Vinyals, Nando de Freitas:
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. ICLR (Poster) 2018 - [i10]Yutian Chen, Yannis M. Assael, Brendan Shillingford, David Budden, Scott E. Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Çaglar Gülçehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas:
Sample Efficient Adaptive Text-to-Speech. CoRR abs/1809.10460 (2018) - [i9]Yutian Chen, Aja Huang, Ziyu Wang, Ioannis Antonoglou, Julian Schrittwieser, David Silver, Nando de Freitas:
Bayesian Optimization in AlphaGo. CoRR abs/1812.06855 (2018) - 2017
- [j3]David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy P. Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis:
Mastering the game of Go without human knowledge. Nat. 550(7676): 354-359 (2017) - [c16]Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matthew M. Botvinick, Nando de Freitas:
Learning to Learn without Gradient Descent by Gradient Descent. ICML 2017: 748-756 - [c15]Scott E. Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio Gomez Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov, Nando de Freitas:
Parallel Multiscale Autoregressive Density Estimation. ICML 2017: 2912-2921 - [i8]Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Jimenez Rezende, Oriol Vinyals, Nando de Freitas:
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. CoRR abs/1710.10304 (2017) - 2016
- [j2]Yutian Chen, Luke Bornn, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling:
Herded Gibbs Sampling. J. Mach. Learn. Res. 17: 10:1-10:29 (2016) - [j1]Anoop Korattikara, Yutian Chen, Max Welling:
Sequential Tests for Large-Scale Learning. Neural Comput. 28(1): 45-70 (2016) - [c14]Yutian Chen, Zoubin Ghahramani:
Scalable Discrete Sampling as a Multi-Armed Bandit Problem. ICML 2016: 2492-2501 - [i7]Yutian Chen, Max Welling:
Herding as a Learning System with Edge-of-Chaos Dynamics. CoRR abs/1602.03014 (2016) - [i6]Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Nando de Freitas:
Learning to Learn for Global Optimization of Black Box Functions. CoRR abs/1611.03824 (2016) - 2015
- [c13]Yarin Gal, Yutian Chen, Zoubin Ghahramani:
Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data. ICML 2015: 645-654 - [c12]Hong Ge, Yutian Chen, Moquan Wan, Zoubin Ghahramani:
Distributed Inference for Dirichlet Process Mixture Models. ICML 2015: 2276-2284 - [i5]Yutian Chen, Zoubin Ghahramani:
Subsampling-Based Approximate Monte Carlo for Discrete Distributions. CoRR abs/1506.09039 (2015) - 2014
- [c11]Anoop Korattikara Balan, Yutian Chen, Max Welling:
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget. ICML 2014: 181-189 - [i4]Yutian Chen, Max Welling:
Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior. CoRR abs/1408.2047 (2014) - 2013
- [c10]Sungjin Ahn, Yutian Chen, Max Welling:
Distributed and Adaptive Darting Monte Carlo through Regenerations. AISTATS 2013: 108-116 - [c9]Yutian Chen, Max Welling:
Evidence Estimation for Bayesian Partially Observed MRFs. AISTATS 2013: 178-186 - [c8]Luke Bornn, Yutian Chen, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling:
Herded Gibbs Sampling. ICLR 2013 - [i3]Anoop Korattikara Balan, Yutian Chen, Max Welling:
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget. CoRR abs/1304.5299 (2013) - 2012
- [c7]Yutian Chen, Max Welling:
Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior. UAI 2012: 174-184 - [i2]Yutian Chen, Max Welling, Alexander J. Smola:
Super-Samples from Kernel Herding. CoRR abs/1203.3472 (2012) - [i1]Yutian Chen, Max Welling:
Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior. CoRR abs/1206.1088 (2012) - 2011
- [c6]Yutian Chen, Andrew Gelfand, Charless C. Fowlkes, Max Welling:
Integrating local classifiers through nonlinear dynamics on label graphs with an application to image segmentation. ICCV 2011: 2635-2642 - 2010
- [c5]Yutian Chen, Max Welling:
Dynamical Products of Experts for Modeling Financial Time Series. ICML 2010: 207-214 - [c4]Andrew Gelfand, Yutian Chen, Laurens van der Maaten, Max Welling:
On Herding and the Perceptron Cycling Theorem. NIPS 2010: 694-702 - [c3]Yutian Chen, Max Welling, Alexander J. Smola:
Super-Samples from Kernel Herding. UAI 2010: 109-116 - [c2]Yutian Chen, Max Welling:
Parametric Herding. AISTATS 2010: 97-104
2000 – 2009
- 2009
- [c1]Yutian Chen, Max Welling:
Bayesian Extreme Components Analysis. IJCAI 2009: 1022-1027
Coauthor Index
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