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Edwin V. Bonilla

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

38

Venues

11

Active years

2006–2025

Best venue rank

A*

Where they publish

Papers

38 indexed papers, newest first.

YearVenueTitleAuthors
2025ICLRVariational Search Distributions.Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla
2025ICMLRnyi Neural Processes.Xuesong Wang, He Zhao, Edwin V. Bonilla
2025ICMLVariational Learning of Fractional Posteriors.Kian Ming A. Chai, Edwin V. Bonilla
2024AISTATSContextual Directed Acyclic Graphs.Ryan Thompson, Edwin V. Bonilla, Robert Kohn
2024ICMLOptimal Transport for Structure Learning Under Missing Data.Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung
2024ICMLParameter Estimation in DAGs from Incomplete Data via Optimal Transport.Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Phung
2023AISTATSRecurrent Neural Networks and Universal Approximation of Bayesian Filters.Adrian N. Bishop, Edwin V. Bonilla
2023ICMLTransformed Distribution Matching for Missing Value Imputation.He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla
2023ICMLFree-Form Variational Inference for Gaussian Process State-Space Models.Xuhui Fan, Edwin V. Bonilla, Terence J. O'Kane, Scott A. Sisson
2023KDDFeature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations.Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung
2022ICMLOptimizing Sequential Experimental Design with Deep Reinforcement Learning.Tom Blau, Edwin V. Bonilla, Iadine Chades, Amir Dezfouli
2022ICMLLearning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks.Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos
2021AISTATSDistribution Regression for Sequential Data.Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry J. Lyons
2021AISTATSSparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations.Simone Rossi, Markus Heinonen, Edwin V. Bonilla, Zheyang Shen, Maurizio Filippone
2021ICMLSigGPDE: Scaling Sparse Gaussian Processes on Sequential Data.Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons
2021ICMLBORE: Bayesian Optimization by Density-Ratio Estimation.Louis C. Tiao, Aaron Klein, Matthias W. Seeger, Edwin V. Bonilla, Cdric Archambeau, Fabio Ramos
2019AISTATSEfficient Inference in Multi-task Cox Process Models.Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla
2019AISTATSCalibrating Deep Convolutional Gaussian Processes.Gia-Lac Tran, Edwin V. Bonilla, John P. Cunningham, Pietro Michiardi, Maurizio Filippone
2018ICMLVariational Network Inference: Strong and Stable with Concrete Support.Amir Dezfouli, Edwin V. Bonilla, Richard Nock
2017AISTATSGray-box Inference for Structured Gaussian Process Models.Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, Novi Quadrianto
2017ICMLRandom Feature Expansions for Deep Gaussian Processes.Kurt Cutajar, Edwin V. Bonilla, Pietro Michiardi, Maurizio Filippone
2017UAIAutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models.Karl Krauth, Edwin V. Bonilla, Kurt Cutajar, Maurizio Filippone
2016ICMLExtended and Unscented Kitchen Sinks.Edwin V. Bonilla, Daniel M. Steinberg, Alistair Reid
2014ICMLFast Allocation of Gaussian Process Experts.Trung V. Nguyen, Edwin V. Bonilla
2014UAICollaborative Multi-output Gaussian Processes.Trung V. Nguyen, Edwin V. Bonilla
2013AISTATSEfficient Variational Inference for Gaussian Process Regression Networks.Trung V. Nguyen, Edwin V. Bonilla
2013IJCAILearning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes.Ehsan Abbasnejad, Scott Sanner, Edwin V. Bonilla, Pascal Poupart
2013IJCAIBayesian Joint Inversions for the Exploration of Earth Resources.Alistair Reid, Simon Timothy O'Callaghan, Edwin V. Bonilla, Lachlan McCalman, Tim Rawling, Fabio Ramos
2012DATEPredicting best design trade-offs: A case study in processor customization.Marcela Zuluaga, Edwin V. Bonilla, Nigel P. Topham
2012ICMLDiscriminative Probabilistic Prototype Learning.Edwin V. Bonilla, Antonio Robles-Kelly
2012WWWNew objective functions for social collaborative filtering.Joseph Noel, Scott Sanner, Khoi-Nguyen Tran, Peter Christen, Lexing Xie, Edwin V. Bonilla, Ehsan Abbasnejad, Nicols Della Penna
2010MICROA Predictive Model for Dynamic Microarchitectural Adaptivity Control.Christophe Dubach, Timothy M. Jones, Edwin V. Bonilla, Michael F. P. O'Boyle
2009CGOAutomatic Feature Generation for Machine Learning Based Optimizing Compilation.Hugh Leather, Edwin V. Bonilla, Michael F. P. O'Boyle
2009MICROPortable compiler optimisation across embedded programs and microarchitectures using machine learning.Christophe Dubach, Timothy M. Jones, Edwin V. Bonilla, Grigori Fursin, Michael F. P. O'Boyle
2007CGORapidly Selecting Good Compiler Optimizations using Performance Counters.John Cavazos, Grigori Fursin, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Olivier Temam
2006CASESAutomatic performance model construction for the fast software exploration of new hardware designs.John Cavazos, Christophe Dubach, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Grigori Fursin, Olivier Temam
2006CGOUsing Machine Learning to Focus Iterative Optimization.Felix V. Agakov, Edwin V. Bonilla, John Cavazos, Bjrn Franke, Grigori Fursin, Michael F. P. O'Boyle, John Thomson, Marc Toussaint, Christopher K. I. Williams
2006ICMLPredictive search distributions.Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle