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06/27/2023
Evaluation of machine learning architectures on the quantification of epistemic and aleatoric uncertainties in complex dynamical systems
Machine learning methods for the construction of data-driven reduced ord...
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09/10/2022
Active Learning for Optimal Intervention Design in Causal Models
An important problem across disciplines is the discovery of intervention...
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08/27/2022
Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models
Not all data are equal. Misleading or unnecessary data can critically hi...
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04/05/2022
Discovering and forecasting extreme events via active learning in neural operators
Extreme events in society and nature, such as pandemic spikes or rogue w...
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03/09/2022
Structure and Distribution Metric for Quantifying the Quality of Uncertainty: Assessing Gaussian Processes, Deep Neural Nets, and Deep Neural Operators for Regression
We propose two bounded comparison metrics that may be implemented to arb...
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09/15/2021
Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes and their dynamics
Solving the population balance equation (PBE) for the dynamics of a disp...
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10/13/2020
Probabilistic characterization of the effect of transient stochastic loads on the fatigue-crack nucleation time
The rainflow counting algorithm for material fatigue is both simple to i...
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05/18/2020
Sparse Methods for Automatic Relevance Determination
This work considers methods for imposing sparsity in Bayesian regression...
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10/09/2019
Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms
How effective are Recurrent Neural Networks (RNNs) in forecasting the sp...
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07/24/2019
Machine Learning the Tangent Space of Dynamical Instabilities from Data
For a large class of dynamical systems, the optimally time-dependent (OT...
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07/17/2019
Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples
For many important problems the quantity of interest (or output) is an u...
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04/19/2018
A sequential sampling strategy for extreme event statistics in nonlinear dynamical systems
We develop a method for the evaluation of extreme event statistics assoc...
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02/21/2018
Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long-Short Term Memory Networks
We introduce a data-driven forecasting method for high dimensional, chao...
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06/01/2017