More from the Same Authors

• 2020 : Scalable Combinatorial Bayesian Optimization with Tractable Statistical models »
  Aryan Deshwal · Syrine Belakaria · Janardhan Rao Doppa
• 2020 : Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations »
  Syrine Belakaria · Aryan Deshwal · Janardhan Rao Doppa
• 2021 : Practical Policy Optimization with PersonalizedExperimentation »
  Mia Garrard · Hanson Wang · Ben Letham · Zehui Wang · Yin Huang · Yichun Hu · Chad Zhou · Norm Zhou · Eytan Bakshy
• 2021 : A Fresh Look at De Novo Molecular Design Benchmarks »
  Austin Tripp · Gregor Simm · José Miguel Hernández-Lobato
• 2021 : Depth Uncertainty Networks for Active Learning »
  Chelsea Murray · James Allingham · Javier Antorán · José Miguel Hernández-Lobato
• 2022 : Preference-Aware Constrained Multi-Objective Bayesian Optimization »
  Alaleh Ahmadianshalchi · Syrine Belakaria · Janardhan Rao Doppa
• 2022 : Sparse Bayesian Optimization »
  Sulin Liu · Qing Feng · David Eriksson · Ben Letham · Eytan Bakshy
• 2022 : Preference-Aware Constrained Multi-Objective Bayesian Optimization »
  Alaleh Ahmadianshalchi · Syrine Belakaria · Janardhan Rao Doppa
• 2022 : Flow Annealed Importance Sampling Bootstrap »
  Laurence Midgley · Vincent Stimper · Gregor Simm · Bernhard Schölkopf · José Miguel Hernández-Lobato
• 2022 : Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction »
  Wenlin Chen · Austin Tripp · José Miguel Hernández-Lobato
• 2022 : Learning Generative Models with Invariance to Symmetries »
  James Allingham · Javier Antorán · Shreyas Padhy · Eric Nalisnick · José Miguel Hernández-Lobato
• 2022 : Preference-Aware Constrained Multi-Objective Bayesian Optimization For Analog Circuit Design »
  Alaleh Ahmadianshalchi · Syrine Belakaria · Jana Doppa
• 2022 : One-Shot Optimal Design for Gaussian Process Analysis of Randomized Experiments »
  Jelena Markovic · Qing Feng · Eytan Bakshy
• 2022 Workshop: New Frontiers in Graph Learning »
  Jiaxuan You · Marinka Zitnik · Rex Ying · Yizhou Sun · Hanjun Dai · Stefanie Jegelka
• 2022 Poster: Local Bayesian optimization via maximizing probability of descent »
  Quan Nguyen · Kaiwen Wu · Jacob Gardner · Roman Garnett
• 2022 Poster: Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks »
  Ching-Yao Chuang · Stefanie Jegelka
• 2022 Poster: Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions »
  Nikolaos Karalias · Joshua Robinson · Andreas Loukas · Stefanie Jegelka
• 2022 Poster: On the generalization of learning algorithms that do not converge »
  Nisha Chandramoorthy · Andreas Loukas · Khashayar Gatmiry · Stefanie Jegelka
• 2022 Poster: Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization »
  Samuel Daulton · Xingchen Wan · David Eriksson · Maximilian Balandat · Michael A Osborne · Eytan Bakshy
• 2022 Poster: Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo »
  Ignacio Peis · Chao Ma · José Miguel Hernández-Lobato
• 2021 Workshop: Deep Generative Models and Downstream Applications »
  José Miguel Hernández-Lobato · Yingzhen Li · Yichuan Zhang · Cheng Zhang · Austin Tripp · Weiwei Pan · Oren Rippel
• 2021 Poster: Functional Variational Inference based on Stochastic Process Generators »
  Chao Ma · José Miguel Hernández-Lobato
• 2021 Poster: Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs »
  Raul Astudillo · Daniel Jiang · Maximilian Balandat · Eytan Bakshy · Peter Frazier
• 2021 Poster: Improving black-box optimization in VAE latent space using decoder uncertainty »
  Pascal Notin · José Miguel Hernández-Lobato · Yarin Gal
• 2021 Poster: Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement »
  Samuel Daulton · Maximilian Balandat · Eytan Bakshy
• 2021 Poster: Bayesian Optimization with High-Dimensional Outputs »
  Wesley Maddox · Maximilian Balandat · Andrew Wilson · Eytan Bakshy
• 2020 Workshop: Machine Learning for Molecules »
  José Miguel Hernández-Lobato · Matt Kusner · Brooks Paige · Marwin Segler · Jennifer Wei
• 2020 : Jose Miguel Hernandez Lobato »
  José Miguel Hernández-Lobato
• 2020 Poster: Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding »
  Gergely Flamich · Marton Havasi · José Miguel Hernández-Lobato
• 2020 Poster: Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization »
  Samuel Daulton · Maximilian Balandat · Eytan Bakshy
• 2020 Poster: Adaptive Sampling for Stochastic Risk-Averse Learning »
  Sebastian Curi · Kfir Y. Levy · Stefanie Jegelka · Andreas Krause
• 2020 Poster: Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining »
  Austin Tripp · Erik Daxberger · José Miguel Hernández-Lobato
• 2020 Poster: Depth Uncertainty in Neural Networks »
  Javier Antorán · James Allingham · José Miguel Hernández-Lobato
• 2020 Poster: VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data »
  Chao Ma · Sebastian Tschiatschek · Richard Turner · José Miguel Hernández-Lobato · Cheng Zhang
• 2020 Poster: BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization »
  Maximilian Balandat · Brian Karrer · Daniel Jiang · Samuel Daulton · Ben Letham · Andrew Wilson · Eytan Bakshy
• 2020 Poster: Barking up the right tree: an approach to search over molecule synthesis DAGs »
  John Bradshaw · Brooks Paige · Matt Kusner · Marwin Segler · José Miguel Hernández-Lobato
• 2020 Poster: Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization »
  Ben Letham · Roberto Calandra · Akshara Rai · Eytan Bakshy
• 2020 Spotlight: Barking up the right tree: an approach to search over molecule synthesis DAGs »
  John Bradshaw · Brooks Paige · Matt Kusner · Marwin Segler · José Miguel Hernández-Lobato
• 2020 Session: Orals & Spotlights Track 15: COVID/Applications/Composition »
  José Miguel Hernández-Lobato · Oliver Stegle
• 2020 Poster: Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees »
  Shali Jiang · Daniel Jiang · Maximilian Balandat · Brian Karrer · Jacob Gardner · Roman Garnett
• 2020 Poster: High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization »
  Qing Feng · Ben Letham · Hongzi Mao · Eytan Bakshy
• 2020 Spotlight: High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization »
  Qing Feng · Ben Letham · Hongzi Mao · Eytan Bakshy
• 2020 Poster: Debiased Contrastive Learning »
  Ching-Yao Chuang · Joshua Robinson · Yen-Chen Lin · Antonio Torralba · Stefanie Jegelka
• 2020 Spotlight: Debiased Contrastive Learning »
  Ching-Yao Chuang · Joshua Robinson · Yen-Chen Lin · Antonio Torralba · Stefanie Jegelka
• 2019 : Invited Speaker: Eytan Bakshy »
  Eytan Bakshy
• 2019 Workshop: Bayesian Deep Learning »
  Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Eric Nalisnick · Zoubin Ghahramani · Kevin Murphy · Max Welling
• 2019 Workshop: Graph Representation Learning »
  Will Hamilton · Rianne van den Berg · Michael Bronstein · Stefanie Jegelka · Thomas Kipf · Jure Leskovec · Renjie Liao · Yizhou Sun · Petar Veličković
• 2019 Poster: Cost Effective Active Search »
  Shali Jiang · Roman Garnett · Benjamin Moseley
• 2019 Poster: Bayesian Batch Active Learning as Sparse Subset Approximation »
  Robert Pinsler · Jonathan Gordon · Eric Nalisnick · José Miguel Hernández-Lobato
• 2019 Poster: Max-value Entropy Search for Multi-Objective Bayesian Optimization »
  Syrine Belakaria · Aryan Deshwal · Janardhan Rao Doppa
• 2019 Poster: Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model »
  Wenbo Gong · Sebastian Tschiatschek · Sebastian Nowozin · Richard Turner · José Miguel Hernández-Lobato · Cheng Zhang
• 2019 Poster: A Model to Search for Synthesizable Molecules »
  John Bradshaw · Brooks Paige · Matt Kusner · Marwin Segler · José Miguel Hernández-Lobato
• 2019 Poster: D-VAE: A Variational Autoencoder for Directed Acyclic Graphs »
  Muhan Zhang · Shali Jiang · Zhicheng Cui · Roman Garnett · Yixin Chen
• 2019 Poster: Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning »
  David Janz · Jiri Hron · Przemysław Mazur · Katja Hofmann · José Miguel Hernández-Lobato · Sebastian Tschiatschek
• 2018 Workshop: Machine Learning for Molecules and Materials »
  José Miguel Hernández-Lobato · Klaus-Robert Müller · Brooks Paige · Matt Kusner · Stefan Chmiela · Kristof Schütt
• 2018 Workshop: Bayesian Deep Learning »
  Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Andrew Wilson · Zoubin Ghahramani · Kevin Murphy · Max Welling
• 2018 Poster: Efficient nonmyopic batch active search »
  Shali Jiang · Gustavo Malkomes · Matthew Abbott · Benjamin Moseley · Roman Garnett
• 2018 Spotlight: Efficient nonmyopic batch active search »
  Shali Jiang · Gustavo Malkomes · Matthew Abbott · Benjamin Moseley · Roman Garnett
• 2018 Poster: Automating Bayesian optimization with Bayesian optimization »
  Gustavo Malkomes · Roman Garnett
• 2018 Poster: Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo »
  Marton Havasi · José Miguel Hernández-Lobato · Juan J. Murillo-Fuentes
• 2017 Workshop: Bayesian Deep Learning »
  Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Andrew Wilson · Andrew Wilson · Diederik Kingma · Zoubin Ghahramani · Kevin Murphy · Max Welling
• 2017 Workshop: Bayesian optimization for science and engineering »
  Ruben Martinez-Cantin · José Miguel Hernández-Lobato · Javier Gonzalez
• 2017 : Closing remarks »
  José Miguel Hernández-Lobato
• 2017 Workshop: Machine Learning for Molecules and Materials »
  Kristof Schütt · Klaus-Robert Müller · Anatole von Lilienfeld · José Miguel Hernández-Lobato · Klaus-Robert Müller · Alan Aspuru-Guzik · Bharath Ramsundar · Matt Kusner · Brooks Paige · Stefan Chmiela · Alexandre Tkatchenko · Anatole von Lilienfeld · Koji Tsuda
• 2016 : Panel Discussion »
  Shakir Mohamed · David Blei · Ryan Adams · José Miguel Hernández-Lobato · Ian Goodfellow · Yarin Gal
• 2016 : Automatic Chemical Design using Variational Autoencoders »
  José Miguel Hernández-Lobato
• 2016 : Alpha divergence minimization for Bayesian deep learning »
  José Miguel Hernández-Lobato
• 2016 Poster: Bayesian optimization for automated model selection »
  Gustavo Malkomes · Charles Schaff · Roman Garnett
• 2015 : *Roman Garnett* Bayesian Quadrature: Lessons Learned and Looking Forwards »
  Roman Garnett
• 2015 Poster: Bayesian Active Model Selection with an Application to Automated Audiometry »
  Jacob Gardner · Gustavo Malkomes · Roman Garnett · Kilian Weinberger · Dennis Barbour · John Cunningham
• 2015 Poster: Stochastic Expectation Propagation »
  Yingzhen Li · José Miguel Hernández-Lobato · Richard Turner
• 2015 Spotlight: Stochastic Expectation Propagation »
  Yingzhen Li · José Miguel Hernández-Lobato · Richard Turner
• 2014 Poster: Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature »
  Tom Gunter · Michael A Osborne · Roman Garnett · Philipp Hennig · Stephen J Roberts
• 2014 Poster: Predictive Entropy Search for Efficient Global Optimization of Black-box Functions »
  José Miguel Hernández-Lobato · Matthew Hoffman · Zoubin Ghahramani
• 2014 Poster: Gaussian Process Volatility Model »
  Yue Wu · José Miguel Hernández-Lobato · Zoubin Ghahramani
• 2014 Spotlight: Predictive Entropy Search for Efficient Global Optimization of Black-box Functions »
  José Miguel Hernández-Lobato · Matthew Hoffman · Zoubin Ghahramani
• 2013 Poster: Learning Feature Selection Dependencies in Multi-task Learning »
  Daniel Hernández-lobato · José Miguel Hernández-Lobato
• 2013 Poster: Gaussian Process Conditional Copulas with Applications to Financial Time Series »
  José Miguel Hernández-Lobato · James R Lloyd · Daniel Hernández-lobato
• 2013 Poster: Σ-Optimality for Active Learning on Gaussian Random Fields »
  Yifei Ma · Roman Garnett · Jeff Schneider
• 2012 Poster: Collaborative Gaussian Processes for Preference Learning »
  Neil Houlsby · José Miguel Hernández-Lobato · Ferenc Huszar · Zoubin Ghahramani
• 2012 Poster: Semi-Supervised Domain Adaptation with Non-Parametric Copulas »
  David Lopez-Paz · José Miguel Hernández-Lobato · Bernhard Schölkopf
• 2012 Spotlight: Semi-Supervised Domain Adaptation with Non-Parametric Copulas »
  David Lopez-Paz · José Miguel Hernández-Lobato · Bernhard Schölkopf
• 2011 Poster: Robust Multi-Class Gaussian Process Classification »
  Daniel Hernández-lobato · José Miguel Hernández-Lobato · Pierre Dupont
• 2007 Poster: Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach »
  José Miguel Hernández-Lobato · Tjeerd M Dijkstra · Tom Heskes