Related Events (a corresponding poster, oral, or spotlight)

• 2007 Spotlight: Bayesian Policy Learning with Trans-Dimensional MCMC »
  Tue. Dec 4th 04:10 -- 04:25 AM Room

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• 2022 : Spectral Diffusion Processes »
  Angus Phillips · Thomas Seror · Michael Hutchinson · Valentin De Bortoli · Arnaud Doucet · Emile Mathieu
• 2022 Spotlight: Lightning Talks 1A-4 »
  Siwei Wang · Jing Liu · Nianqiao Ju · Shiqian Li · Eloïse Berthier · Muhammad Faaiz Taufiq · Arsene Fansi Tchango · Chen Liang · Chulin Xie · Jordan Awan · Jean-Francois Ton · Ziad Kobeissi · Wenguan Wang · Xinwang Liu · Kewen Wu · Rishab Goel · Jiaxu Miao · Suyuan Liu · Julien Martel · Ruobin Gong · Francis Bach · Chi Zhang · Rob Cornish · Sanmi Koyejo · Zhi Wen · Yee Whye Teh · Yi Yang · Jiaqi Jin · Bo Li · Yixin Zhu · Vinayak Rao · Wenxuan Tu · Gaetan Marceau Caron · Arnaud Doucet · Xinzhong Zhu · Joumana Ghosn · En Zhu
• 2022 Spotlight: Conformal Off-Policy Prediction in Contextual Bandits »
  Muhammad Faaiz Taufiq · Jean-Francois Ton · Rob Cornish · Yee Whye Teh · Arnaud Doucet
• 2022 Poster: Conformal Off-Policy Prediction in Contextual Bandits »
  Muhammad Faaiz Taufiq · Jean-Francois Ton · Rob Cornish · Yee Whye Teh · Arnaud Doucet
• 2022 Poster: A Continuous Time Framework for Discrete Denoising Models »
  Andrew Campbell · Joe Benton · Valentin De Bortoli · Thomas Rainforth · George Deligiannidis · Arnaud Doucet
• 2022 Poster: Score-Based Diffusion meets Annealed Importance Sampling »
  Arnaud Doucet · Will Grathwohl · Alexander Matthews · Heiko Strathmann
• 2022 Poster: A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs »
  Fabian Falck · Christopher Williams · Dominic Danks · George Deligiannidis · Christopher Yau · Chris C Holmes · Arnaud Doucet · Matthew Willetts
• 2022 Poster: Riemannian Score-Based Generative Modelling »
  Valentin De Bortoli · Emile Mathieu · Michael Hutchinson · James Thornton · Yee Whye Teh · Arnaud Doucet
• 2022 Poster: Towards Learning Universal Hyperparameter Optimizers with Transformers »
  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
• 2021 Test Of Time: Online Learning for Latent Dirichlet Allocation »
  Matthew Hoffman · Francis Bach · David Blei
• 2020 Poster: Modular Meta-Learning with Shrinkage »
  Yutian Chen · Abram Friesen · Feryal Behbahani · Arnaud Doucet · David Budden · Matthew Hoffman · Nando de Freitas
• 2020 Spotlight: Modular Meta-Learning with Shrinkage »
  Yutian Chen · Abram Friesen · Feryal Behbahani · Arnaud Doucet · David Budden · Matthew Hoffman · Nando de Freitas
• 2020 Poster: RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning »
  Caglar Gulcehre · Ziyu Wang · Alexander Novikov · Thomas Paine · Sergio Gómez · Konrad Zolna · Rishabh Agarwal · Josh Merel · Daniel Mankowitz · Cosmin Paduraru · Gabriel Dulac-Arnold · Jerry Li · Mohammad Norouzi · Matthew Hoffman · Nicolas Heess · Nando de Freitas
• 2019 Poster: Augmented Neural ODEs »
  Emilien Dupont · Arnaud Doucet · Yee Whye Teh
• 2018 Poster: Hamiltonian Variational Auto-Encoder »
  Anthony Caterini · Arnaud Doucet · Dino Sejdinovic
• 2017 Poster: Filtering Variational Objectives »
  Chris Maddison · John Lawson · George Tucker · Nicolas Heess · Mohammad Norouzi · Andriy Mnih · Arnaud Doucet · Yee Teh
• 2017 Poster: Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling »
  Andrei-Cristian Barbos · Francois Caron · Jean-François Giovannelli · Arnaud Doucet
• 2016 Poster: Learning to learn by gradient descent by gradient descent »
  Marcin Andrychowicz · Misha Denil · Sergio Gómez · Matthew Hoffman · David Pfau · Tom Schaul · Nando de Freitas
• 2016 Poster: Learning to Communicate with Deep Multi-Agent Reinforcement Learning »
  Jakob Foerster · Yannis Assael · Nando de Freitas · Shimon Whiteson
• 2015 : Information based methods for Black-box Optimization »
  Matthew Hoffman
• 2015 Workshop: Scalable Monte Carlo Methods for Bayesian Analysis of Big Data »
  Babak Shahbaba · Yee Whye Teh · Max Welling · Arnaud Doucet · Christophe Andrieu · Sebastian J. Vollmer · Pierre Jacob
• 2015 Poster: Expectation Particle Belief Propagation »
  Thibaut Lienart · Yee Whye Teh · Arnaud Doucet
• 2014 Workshop: Bayesian Optimization in Academia and Industry »
  Zoubin Ghahramani · Ryan Adams · Matthew Hoffman · Kevin Swersky · Jasper Snoek
• 2014 Poster: Asynchronous Anytime Sequential Monte Carlo »
  Brooks Paige · Frank Wood · Arnaud Doucet · Yee Whye Teh
• 2014 Oral: Asynchronous Anytime Sequential Monte Carlo »
  Brooks Paige · Frank Wood · Arnaud Doucet · Yee Whye Teh
• 2014 Poster: Predictive Entropy Search for Efficient Global Optimization of Black-box Functions »
  José Miguel Hernández-Lobato · Matthew Hoffman · Zoubin Ghahramani
• 2014 Spotlight: Predictive Entropy Search for Efficient Global Optimization of Black-box Functions »
  José Miguel Hernández-Lobato · Matthew Hoffman · Zoubin Ghahramani
• 2014 Poster: Distributed Parameter Estimation in Probabilistic Graphical Models »
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• 2013 Workshop: Bayesian Optimization in Theory and Practice »
  Matthew Hoffman · Jasper Snoek · Nando de Freitas · Michael A Osborne · Ryan Adams · Sebastien Bubeck · Philipp Hennig · Remi Munos · Andreas Krause
• 2013 Workshop: Deep Learning »
  Yoshua Bengio · Hugo Larochelle · Russ Salakhutdinov · Tomas Mikolov · Matthew D Zeiler · David Mcallester · Nando de Freitas · Josh Tenenbaum · Jian Zhou · Volodymyr Mnih
• 2011 Workshop: Bayesian optimization, experimental design and bandits: Theory and applications »
  Nando de Freitas · Roman Garnett · Frank R Hutter · Michael A Osborne
• 2010 Session: Spotlights Session 10 »
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• 2010 Session: Oral Session 12 »
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• 2009 Workshop: Adaptive Sensing, Active Learning, and Experimental Design »
  Rui M Castro · Nando de Freitas · Ruben Martinez-Cantin
• 2009 Poster: Bayesian Nonparametric Models on Decomposable Graphs »
  Francois Caron · Arnaud Doucet
• 2009 Tutorial: Sequential Monte-Carlo Methods »
  Arnaud Doucet · Nando de Freitas
• 2008 Poster: An interior-point stochastic approximation method and an L1-regularized delta rule »
  Peter Carbonetto · Mark Schmidt · Nando de Freitas
• 2008 Oral: An interior-point stochastic approximation method and an L1-regularized delta rule »
  Peter Carbonetto · Mark Schmidt · Nando de Freitas
• 2008 Demonstration: Worio: A Web-Scale Machine Learning System »
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• 2007 Poster: Active Preference Learning with Discrete Choice Data »
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• 2006 Poster: Conditional mean field »
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