Yutian Chen

Publications ( bibtex, Google Scholar )

• Ph.D. Dissertation, 2013

  1. Herding: Driving Deterministic Dynamics to Learn and Sample Probabilistic Models. pdf

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• Book Chapters

  1. Yutian Chen and Max Welling
     Herding as a Learning System with Edge-of-Chaos Dynamics.
     In: Perturbations, Optimization, and Statistics. T. Hazan, G. Papandreou and D. Tarlow (Eds) 2016. Chapter, Book
  2. Yutian Chen, Andrew Gelfand and Max Welling
     Herding for Structured Prediction.
     In: Advanced Structured Prediction. S. Nowozin, P. Gehler, J. Jancsary, C. Lampert (Eds) 2014. Chapter, Book

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• Journal Papers

  1. D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis
     Mastering the game of go without human knowledge..
     Nature, 550(7676):354–359, October 2017. link
  2. Yutian Chen, Luke Bornn, Nando de Freitas, Mareija Eskelin, Jing Fang and Max Welling
     Herded Gibbs Sampling.
     Journal of Machine Learning Research (JMLR), 17(10): 1−29, 2016. link pdf
  3. Anoop Korattikara, Yutian Chen and Max Welling
     Sequential Tests for Large-Scale Learning.
     Neural Computation, 28.1: 45-70, 2016. link pdf
  4. Meng Zhu, Chang-song Liu, Yutian Chen and Yan-ming Zou
     Combined Recognition System for Handwritten Pinyin.
     Computer Engineering, 36(7): 170-172, 2010. pdf

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• Conference/Workshop Papers/Technical Reports

  1. Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram Friesen, Junhyuk Oh, Yutian Chen.
     Introducing Symmetries to Black Box Meta Reinforcement Learning.
     Under review. arXiv
  2. Yutian Chen, Liyuan Xu, Caglar Gulcehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet.
     On Instrumental Variable Regression for Deep Offline Policy Evaluation.
     Under review. arXiv
  3. Michalis K. Titsias, Jakub Sygnowski, Yutian Chen.
     Sequential Changepoint Detection in Neural Networks with Checkpoints.
     Under review. arXiv
  4. Ksenia Konyushkova*, Yutian Chen*, Tom Le Paine, Caglar Gulcehre, Cosmin Paduraru, Daniel J Mankowitz, Misha Denil, Nando de Freitas. (*: equal contribution)
     Active Offline Policy Selection.
     Accepted by Neural Information Processing Systems (NeurIPS), 2021. arXiv
  5. Caglar Gulcehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew Hoffman, Razvan Pascanu, Nando de Freitas.
     Regularized Behavior Value Estimation.
     Technical report, 2021. arXiv
  6. 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, Thomas Paine.
     Benchmarks for Deep Off-Policy Evaluation.
     International Conference on Learning Representations (ICLR), 2021. open review arXiv
  7. Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton.
     Learning Deep Features in Instrumental Variable Regression.
     International Conference on Learning Representations (ICLR), 2021. open review arXiv
  8. Yiling Huang, Yutian Chen, Jason Pelecanos, Quan Wang.
     Synth2Aug: Cross-domain Speaker Recognition with TTS Synthesized Speech..
     IEEE Spoken Language Technology Workshop (IEEE SLT), 2021.
  9. Yi Yang, Brendan Shillingford, Yannis 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.
     Tech report, 2020. arXiv
  10. Yutian Chen, Abram L. Friesen, Feryal Behbahani, Arnaud Doucet, David Budden, Matthew W. Hoffman, Nando de Freitas.
      Modular Meta-Learning with Shrinkage.
      Neural Information Processing Systems (NeurIPS), 2020 as a spotlight talk. arXiv
  11. Yutian Chen, Yannis M. Assael, Brendan Shillingford, David Budden, Scott E. Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Caglar Gulcehre, Aa ̈ron van den Oord, Oriol Vinyals, and Nando de Freitas.
      Sample Efficient Adaptive Text-to-Speech.
      International Conference on Learning Representations (ICLR), 2019. open review arXiv
  12. Yutian Chen, Aja Huang, Ziyu Wang, Ioannis Antonoglou, Julian Schrittwieser, David Silver, and Nando de Freitas
      Bayesian Optimization in AlphaGo.
      Technical report, 2018. arXiv
  13. Vikash K. Mansinghka, Ulrich Schaechtle, Shivam Handa, Alexey Radul, Yutian Chen, and Martin Rinard
      Probabilistic Programming with Programmable Inference.
      In Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2018. ACM, New York, NY, USA, 603-616. link pdf
  14. Scott Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Rezende, Oriol Vinyals, and Nando de Freitas
      Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions.
      International Conference on Learning Representations (ICLR), 2018. open review arXiv
  15. Scott Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio Gómez Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov, and Nando de Freitas
      Parallel Multiscale Autoregressive Density Estimation.
      International Conference on Machine Learning (ICML), 2017. pdf supplementary
  16. Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matt Botvinick and Nando de Freitas
      Learning to Learn without Gradient Descent by Gradient Descent.
      International Conference on Machine Learning (ICML), 2017. pdf
  17. Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap and Nando de Freitas
      Learning to Learn for Global Optimization of Black Box Functions.
      Deep Reinforcement Learning Workshop, NIPS 2016. arXiv pdf
  18. Yutian Chen and Zoubin Ghahramani
      Scalable Discrete Sampling as a Multi-Armed Bandit Problem.
      International Conference on Machine Learning (ICML), 2016. link pdf supplmentary
  19. Yutian Chen, Vikash Mansinghka and Zoubin Ghahramani
      Sublinear Approximate Inference for Probabilistic Programs.
      Technical report, 2015. arXiv
  20. Yarin Gal, Yutian Chen and Zoubin Ghahramani
      Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data.
      International Conference on Machine Learning (ICML), 2015. link pdf supplementary
  21. Hong Ge, Yutian Chen, Moquan Wan and Zoubin Ghahramani
      Distributed Inference for Dirichlet Process Mixture Models.
      International Conference on Machine Learning (ICML), 2015. link pdf
  22. Roger Frigola, Yutian Chen and Carl E. Rasmussen
      Variational Gaussian Process State-Space Models.
      Neural Information Processing Systems (NIPS), 2014. pdf
  23. Anoop Korattikara, Yutian Chen and Max Welling
      Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget.
      International Conference on Machine Learning (ICML), 2014. pdf supplementary
      Version at JSM, 2013: pdf
      Version at NIPS Workshop: Pobabilistic Models for Big Data, 2013: pdf
  24. Luke Bornn, Yutian Chen, Nando de Freitas, Mareija Eskelin, Jing Fang and Max Welling
      Herded Gibbs Sampling.
      International Conference on Learning Representations (ICLR), 2013. pdf
  25. Sungjin Ahn, Yutian Chen and Max Welling
      Distributed and Adaptive Darting Monte Carlo through Regenerations.
      Artificial Intelligence and Statistics (AISTATS), 2013. pdf
  26. Yutian Chen and Max Welling
      Evidence Estimation for Partially Observed MRFs.
      Artificial Intelligence and Statistics (AISTATS), 2013. pdf
  27. Yutian Chen and Max Welling
      Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior.
      Conference on Uncertainty in Artificial Intelligence (UAI),2012. pdf
  28. Yutian Chen, Andrew Gelfand, Charless C. Fowlkes and Max Welling
      Integrating Local Classifiers through Nonlinear Dynamics on Label Graphs with an Application to Image Segmentation.
      International Conference on Computer Vision (ICCV), 2011. pdf
  29. Andrew E. Gelfand, Laurens van der Maaten, Yutian Chen and Max Welling
      On Herding and the Perceptron Cycling Theorem.
      Neural Information Processing Systems (NIPS), 2010. pdf
  30. Yutian Chen, Max Welling and Alex Smola
      Super-Samples from Kernel Herding.
      Conference on Uncertainty in Artificial Intelligence (UAI), 2010. pdf code
  31. Yutian Chen and Max Welling
      Dynamical Products of Experts for Modeling Financial Time Series.
      International Conference on Machine Learning (ICML), 2010. pdf
  32. Yutian Chen and Max Welling
      Parametric Herding.
      Artificial Intelligence and Statistics (AISTATS), 2010. pdf
  33. Max Welling and Yutian Chen
      Statistical Inference Using Weak Chaos and Infinite Memory.
      Proceedings of the Int'l Workshop on Statistical-Mechanical Informatics (IW-SMI), 2010. pdf
  34. Yutian Chen and Max Welling
      Bayesian Extreme Components Analysis.
      International Joint Conferences on Artificial Intelligence (IJCAI), 2009. pdf code