Edwin Bonilla

Latest

• Distribution Regression for Sequential Data
• Sparse Gaussian processes revisited: Bayesian approaches to inducing-variable approximations
• Rethinking Sparse Gaussian Processes: Bayesian Approaches to Inducing-Variable Approximations
• Efficient Inference in Multi-task Cox Process Models
• Variational Network Inference: Strong and Stable with Concrete Support
• Scalable Gaussian process models for solar power forecasting
• Extended and unscented kitchen sinks
• Automatic feature generation for machine learning--based optimising compilation
• Fast allocation of Gaussian process experts
• Inference Engine Final Report to ARENA Inference Engine Final Report to ARENA
• Bayesian joint inversions for the exploration of earth resources
• Efficient Variational Inference for Gaussian Process Regression Networks
• Bayesian data fusion for geothermal exploration
• Discriminative probabilistic prototype learning
• Predicting best design trade-offs: A case study in processor customization
• Automatic feature generation for machine learning based optimizing compilation
• MILEPOST GCC: machine learning based research compiler
• Rapidly selecting good compiler optimizations using performance counters
• Automatic performance model construction for the fast software exploration of new hardware designs
• Using machine learning to focus iterative optimization