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04/08/2023
Polygonizer: An auto-regressive building delineator
In geospatial planning, it is often essential to represent objects in a ...
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03/20/2023
Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery
We present a novel pipeline for learning the conditional distribution of...
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01/14/2023
On the role of Model Uncertainties in Bayesian Optimization
Bayesian optimization (BO) is a popular method for black-box optimizatio...
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12/02/2022
SolarDK: A high-resolution urban solar panel image classification and localization dataset
The body of research on classification of solar panel arrays from aerial...
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03/29/2022
Robust, Automated, and Accurate Black-box Variational Inference
Black-box variational inference (BBVI) now sees widespread use in machin...
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03/01/2021
Challenges and Opportunities in High-dimensional Variational Inference
We explore the limitations of and best practices for using black-box var...
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09/01/2020
Robust, Accurate Stochastic Optimization for Variational Inference
We consider the problem of fitting variational posterior approximations ...
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07/12/2020
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
We formulate approximate Bayesian inference in non-conjugate temporal an...
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03/25/2020
Preferential Batch Bayesian Optimization
Most research in Bayesian optimization (BO) has focused on direct feedba...
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01/03/2020
Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data
Recently, new methods for model assessment, based on subsampling and pos...
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11/07/2019
Gaussian process with derivative information for the analysis of the sunlight adverse effects on color of rock art paintings
Microfading Spectrometry (MFS) is a method for assessing light sensitivi...
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10/17/2019
Ranking variables and interactions using predictive uncertainty measures
For complex nonlinear supervised learning models, assessing the relevanc...
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04/24/2019
Bayesian leave-one-out cross-validation for large data
Model inference, such as model comparison, model checking, and model sel...
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01/31/2019
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
A typical audio signal processing pipeline includes multiple disjoint an...
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11/06/2018
Unifying Probabilistic Models for Time-Frequency Analysis
In audio signal processing, probabilistic time-frequency models have man...
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12/21/2017
Model selection for Gaussian processes utilizing sensitivity of posterior predictive distribution
We propose two novel methods for simplifying Gaussian process (GP) model...
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09/15/2015
Bayesian inference for spatio-temporal spike-and-slab priors
In this work, we address the problem of solving a series of underdetermi...
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08/19/2015