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07/05/2023
Table inference for combinatorial origin-destination choices in agent-based population synthesis
A key challenge in agent-based mobility simulations is the synthesis of ...
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06/02/2023
Robust Bayesian Inference for Measurement Error Models
Measurement error occurs when a set of covariates influencing a response...
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05/07/2023
Quantifying Consistency and Information Loss for Causal Abstraction Learning
Structural causal models provide a formalism to express causal relations...
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01/14/2023
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions
An abstraction can be used to relate two structural causal models repres...
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08/23/2022
Causal Entropy Optimization
We study the problem of globally optimizing the causal effect on a targe...
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08/01/2022
Towards Computing an Optimal Abstraction for Structural Causal Models
Working with causal models at different levels of abstraction is an impo...
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02/09/2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap
Simulator-based models are models for which the likelihood is intractabl...
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01/22/2022
Uncertainty-aware deep learning methods for robust diabetic retinopathy classification
Automatic classification of diabetic retinopathy from retinal images has...
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11/02/2021
Spatio-Temporal Variational Gaussian Processes
We introduce a scalable approach to Gaussian process inference that comb...
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10/26/2021
Dynamic Causal Bayesian Optimization
This paper studies the problem of performing a sequence of optimal inter...
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09/08/2021
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes
Stochastic processes are random variables with values in some space of p...
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08/05/2021
A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities
We study the problem of estimating potential revenue or demand at busine...
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05/10/2021
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Making predictions and quantifying their uncertainty when the input data...
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12/08/2020
An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System
One of the Greater London Authority's (GLA) response to the COVID-19 pan...
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12/07/2020
Near Real-Time Social Distancing in London
During the COVID-19 pandemic, policy makers at the Greater London Author...
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11/03/2020
Transforming Gaussian Processes With Normalizing Flows
Gaussian Processes (GPs) can be used as flexible, non-parametric functio...
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09/27/2020
Multi-task Causal Learning with Gaussian Processes
This paper studies the problem of learning the correlation structure of ...
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08/24/2020
Exoplanet Validation with Machine Learning: 50 new validated Kepler planets
Over 30 'validation', where the statistical likelihood of a transit aris...
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06/28/2020
Variational Autoencoding of PDE Inverse Problems
Specifying a governing physical model in the presence of missing physics...
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02/23/2020
Generalized Bayesian Filtering via Sequential Monte Carlo
We introduce a framework for inference in general state-space hidden Mar...
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10/09/2019
Probabilistic sequential matrix factorization
We introduce the probabilistic sequential matrix factorization (PSMF) me...
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06/19/2019
Multi-resolution Multi-task Gaussian Processes
We consider evidence integration from potentially dependent observation ...
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06/18/2019
On the Constrained Least-cost Tour Problem
We introduce the Constrained Least-cost Tour (CLT) problem: given an und...
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06/07/2019
Structured Variational Inference in Continuous Cox Process Models
We propose a scalable framework for inference in an inhomogeneous Poisso...
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04/03/2019
Generalized Variational Inference
This paper introduces a generalized representation of Bayesian inference...
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06/06/2018
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences
We present the very first robust Bayesian Online Changepoint Detection a...
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05/14/2018