Bayesian Extreme Components Analysis. - Yutian Chen 001; Max Welling (IJCAI, 2009)

Dynamical Products of Experts for Modeling Financial Time Series. - Yutian Chen 001; Max Welling (ICML, 2010)

On Herding and the Perceptron Cycling Theorem. - Andrew Gelfand; Yutian Chen 001; Laurens van der Maaten; Max Welling (NIPS, 2010)

Super-Samples from Kernel Herding. - Yutian Chen 001; Max Welling; Alexander J. Smola (UAI, 2010)

Parametric Herding. - Yutian Chen 001; Max Welling (AISTATS, 2010)

Integrating local classifiers through nonlinear dynamics on label graphs with an application to image segmentation. - Yutian Chen 001; Andrew Gelfand; Charless C. Fowlkes; Max Welling (ICCV, 2011)

Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior. - Yutian Chen 001; Max Welling (UAI, 2012)

Distributed and Adaptive Darting Monte Carlo through Regenerations. - Sungjin Ahn; Yutian Chen 001; Max Welling (AISTATS, 2013)

Evidence Estimation for Bayesian Partially Observed MRFs. - Yutian Chen 001; Max Welling (AISTATS, 2013)

Herded Gibbs Sampling - Luke Bornn; Yutian Chen 001; Nando de Freitas; Mareija Eskelin; Jing Fang; Max Welling (ICLR, 2013)

Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget. - Anoop Korattikara Balan; Yutian Chen 001; Max Welling (ICML, 2014)

Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data. - Yarin Gal; Yutian Chen 001; Zoubin Ghahramani (ICML, 2015)

Distributed Inference for Dirichlet Process Mixture Models. - Hong Ge; Yutian Chen 001; Moquan Wan; Zoubin Ghahramani (ICML, 2015)

Subsampling-Based Approximate Monte Carlo for Discrete Distributions. - Yutian Chen 001; Zoubin Ghahramani (CoRR, 2015)

Scalable Discrete Sampling as a Multi-Armed Bandit Problem. - Yutian Chen 001; Zoubin Ghahramani (ICML, 2016)

Learning to Learn for Global Optimization of Black Box Functions. - Yutian Chen 001; Matthew W. Hoffman; Sergio Gomez Colmenarejo; Misha Denil; Timothy P. Lillicrap; Nando de Freitas (CoRR, 2016)

Herding as a Learning System with Edge-of-Chaos Dynamics. - Yutian Chen 001; Max Welling (CoRR, 2016)

Sequential Tests for Large-Scale Learning. - Anoop Korattikara; Yutian Chen 001; Max Welling (Neural Comput., 2016)

Learning to Learn without Gradient Descent by Gradient Descent. - Yutian Chen 001; Matthew W. Hoffman; Sergio Gomez Colmenarejo; Misha Denil; Timothy P. Lillicrap; Matthew M. Botvinick; Nando de Freitas (ICML, 2017)

Parallel Multiscale Autoregressive Density Estimation. - Scott E. Reed; Aäron van den Oord; Nal Kalchbrenner; Sergio Gomez Colmenarejo; Ziyu Wang 001; Yutian Chen 001; Dan Belov; Nando de Freitas (ICML, 2017)

Mastering the game of Go without human knowledge. - David Silver; Julian Schrittwieser; Karen Simonyan; Ioannis Antonoglou; Aja Huang; Arthur Guez; Thomas Hubert; Lucas Baker; Matthew Lai; Adrian Bolton; Yutian Chen 001; Timothy P. Lillicrap; et al. (Nat., 2017)

Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. - Scott E. Reed; Yutian Chen 001; Thomas Paine; Aäron van den Oord; S. M. Ali Eslami; Danilo J. Rezende; Oriol Vinyals; Nando de Freitas (ICLR (Poster), 2018)

Bayesian Optimization in AlphaGo. - Yutian Chen 001; Aja Huang; Ziyu Wang 001; Ioannis Antonoglou; Julian Schrittwieser; David Silver; Nando de Freitas (CoRR, 2018)

Sample Efficient Adaptive Text-to-Speech. - Yutian Chen 001; 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; et al. (ICLR (Poster), 2019)

Modular Meta-Learning with Shrinkage. - Yutian Chen 001; Abram L. Friesen; Feryal M. P. Behbahani; Arnaud Doucet; David Budden; Matthew Hoffman 002; Nando de Freitas (NeurIPS, 2020)

Large-scale multilingual audio visual dubbing. - Yi Yang 007; Brendan Shillingford; Yannis M. Assael; Miaosen Wang; Wendi Liu; Yutian Chen 001; Yu Zhang; Eren Sezener; Luis C. Cobo; Misha Denil; Yusuf Aytar; Nando de Freitas (CoRR, 2020)

Benchmarks for Deep Off-Policy Evaluation. - Justin Fu; Mohammad Norouzi 002; Ofir Nachum; George Tucker; Ziyu Wang 001; Alexander Novikov 001; Mengjiao Yang 001; Michael R. Zhang; Yutian Chen 001; Aviral Kumar; Cosmin Paduraru; Sergey Levine; et al. (ICLR, 2021)

Learning Deep Features in Instrumental Variable Regression. - Liyuan Xu; Yutian Chen 001; Siddarth Srinivasan; Nando de Freitas; Arnaud Doucet; Arthur Gretton (ICLR, 2021)

Active Offline Policy Selection. - Ksenia Konyushkova; Yutian Chen 001; Thomas Paine; Çaglar Gülçehre; Cosmin Paduraru; Daniel J. Mankowitz; Misha Denil; Nando de Freitas (NeurIPS, 2021)

Regularized Behavior Value Estimation. - Çaglar Gülçehre; Sergio Gómez Colmenarejo; Ziyu Wang 001; Jakub Sygnowski; Thomas Paine; Konrad Zolna; Yutian Chen 001; Matthew W. Hoffman; Razvan Pascanu; Nando de Freitas (CoRR, 2021)

Shaking the foundations: delusions in sequence models for interaction and control. - 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; et al. (CoRR, 2021)

Introducing Symmetries to Black Box Meta Reinforcement Learning. - Louis Kirsch; Sebastian Flennerhag; Hado van Hasselt; Abram L. Friesen; Junhyuk Oh; Yutian Chen 001 (AAAI, 2022)

Towards Learning Universal Hyperparameter Optimizers with Transformers. - Yutian Chen 001; Xingyou Song; Chansoo Lee; Zi Wang; Richard Zhang 003; David Dohan; Kazuya Kawakami; Greg Kochanski; Arnaud Doucet; Marc'Aurelio Ranzato; Sagi Perel; Nando de Freitas (NeurIPS, 2022)

Multi-step Planning for Automated Hyperparameter Optimization with OptFormer. - Lucio M. Dery; Abram L. Friesen; Nando de Freitas; Marc'Aurelio Ranzato; Yutian Chen 001 (CoRR, 2022)

NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuang Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (CoRR, 2022)

On Instrumental Variable Regression for Deep Offline Policy Evaluation. - Yutian Chen 001; Liyuan Xu; Çaglar Gülçehre; Tom Le Paine; Arthur Gretton; Nando de Freitas; Arnaud Doucet (J. Mach. Learn. Res., 2022)

A Generalist Agent. - Scott E. Reed; Konrad Zolna; Emilio Parisotto; Sergio Gómez Colmenarejo; Alexander Novikov 001; Gabriel Barth-Maron; Mai Gimenez; Yury Sulsky; Jackie Kay; Jost Tobias Springenberg; Tom Eccles; Jake Bruce; et al. (Trans. Mach. Learn. Res., 2022)

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. - Robert Tjarko Lange; Tom Schaul; Yutian Chen 001; Chris Lu 001; Tom Zahavy; Valentin Dalibard; Sebastian Flennerhag (GECCO, 2023)

Discovering Evolution Strategies via Meta-Black-Box Optimization. - Robert Tjarko Lange; Tom Schaul; Yutian Chen 001; Tom Zahavy; Valentin Dalibard; Chris Lu 001; Satinder Singh 001; Sebastian Flennerhag (GECCO Companion, 2023)

π2vec: Policy Representations with Successor Features. - Gianluca Scarpellini; Ksenia Konyushkova; Claudio Fantacci; Tom Le Paine; Yutian Chen 001; Misha Denil (CoRR, 2023)

Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuan Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (J. Mach. Learn. Res., 2023)

π2vec: Policy Representation with Successor Features. - Gianluca Scarpellini; Ksenia Konyushkova; Claudio Fantacci; Thomas Paine; Yutian Chen 001; Misha Denil (ICLR, 2024)

Position: Leverage Foundational Models for Black-Box Optimization. - Xingyou Song; Yingtao Tian; Robert Tjarko Lange; Chansoo Lee; Yujin Tang; Yutian Chen 001 (ICML, 2024)

GATS: Gather-Attend-Scatter. - Konrad Zolna; Serkan Cabi; Yutian Chen 001; Eric Lau; Claudio Fantacci; Jurgis Pasukonis; Jost Tobias Springenberg; Sergio Gomez Colmenarejo (CoRR, 2024)

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. - Soham De; Samuel L. Smith; Anushan Fernando; Aleksandar Botev; George-Cristian Muraru; Albert Gu; Ruba Haroun; Leonard Berrada; Yutian Chen 001; Srivatsan Srinivasan; Guillaume Desjardins; Arnaud Doucet; et al. (CoRR, 2024)

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. - 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; et al. (CoRR, 2024)

Predicting from Strings: Language Model Embeddings for Bayesian Optimization. - Tung Nguyen; Qiuyi Zhang 001; Bangding Yang; Chansoo Lee; Jörg Bornschein; Yingjie Miao; Sagi Perel; Yutian Chen 001; Xingyou Song (CoRR, 2024)

TRecViT: A Recurrent Video Transformer. - Viorica Patraucean; Xu Owen He; Joseph Heyward; Chuhan Zhang; Mehdi S. M. Sajjadi; George-Cristian Muraru; Artem Zholus; Mahdi Karami; Ross Goroshin; Yutian Chen 001; Simon Osindero; João Carreira 001; et al. (CoRR, 2024)

OmniPred: Language Models as Universal Regressors. - Xingyou Song; Oscar Li; Chansoo Lee; Bangding Yang; Daiyi Peng; Sagi Perel; Yutian Chen 001 (Trans. Mach. Learn. Res., 2024)