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06/08/2023
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs
We present AircraftVerse, a publicly available aerial vehicle design dat...
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11/11/2022
Design of Unmanned Air Vehicles Using Transformer Surrogate Models
Computer-aided design (CAD) is a promising new area for the application ...
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02/08/2022
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning
Bayesian methods hold significant promise for improving the uncertainty ...
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10/14/2021
HumBugDB: A Large-scale Acoustic Mosquito Dataset
This paper presents the first large-scale multi-species dataset of acous...
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12/11/2020
Better call Surrogates: A hybrid Evolutionary Algorithm for Hyperparameter optimization
In this paper, we propose a surrogate-assisted evolutionary algorithm (E...
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10/14/2020
Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting
Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) appro...
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07/08/2020
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks
While deep learning methods continue to improve in predictive accuracy o...
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01/14/2020
HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset
Mosquitoes are the only known vector of malaria, which leads to hundreds...
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10/14/2019
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo
We introduce a recent symplectic integration scheme derived for solving ...
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05/25/2019
An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval
Machine learning is now used in many areas of astrophysics, from detecti...
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12/12/2018
Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity
As societies around the world are ageing, the number of Alzheimer's dise...
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11/08/2018
Bayesian Deep Learning for Exoplanet Atmospheric Retrieval
Over the past decade, the study of exoplanets has shifted from their det...
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05/10/2018
Loss-Calibrated Approximate Inference in Bayesian Neural Networks
Current approaches in approximate inference for Bayesian neural networks...
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02/22/2018
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus
In systems of multiple agents, identifying the cause of observed agent d...
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09/07/2017
