Search Results for author: Peter K. Kitanidis

Found 7 papers, 2 papers with code

Multi-fidelity Hamiltonian Monte Carlo

no code implementations8 May 2024 Dhruv V. Patel, Jonghyun Lee, Matthew W. Farthing, Peter K. Kitanidis, Eric F. Darve

In this multi-fidelity algorithm, the acceptance probability is computed in the first stage via a standard HMC proposal using an inexpensive differentiable surrogate model, and if the proposal is accepted, the posterior is evaluated in the second stage using the high-fidelity (HF) numerical solver.

Effective approaches to disaster evacuation during a COVID-like pandemic

no code implementations29 Aug 2022 Yi-Lin Tsai, Dymasius Y. Sitepu, Karyn E. Chappell, Rishi P. Mediratta, C. Jason Wang, Peter K. Kitanidis, Christopher B. Field

Therefore, we applied an age-structured epidemiological model, known as the Susceptible-Exposed-Infectious-Recovered (SEIR) model, to investigate to what extent different vaccine uptake levels and the Diversion protocol implemented in Taiwan decrease infections and delay pandemic peak occurrences.

Improving debris flow evacuation alerts in Taiwan using machine learning

no code implementations27 Aug 2022 Yi-Lin Tsai, Jeremy Irvin, Suhas Chundi, Andrew Y. Ng, Christopher B. Field, Peter K. Kitanidis

Towards improving this system, we implemented five machine learning models that input historical rainfall data and predict whether a debris flow will occur within a selected time.

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

1 code implementation23 Nov 2021 Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew Farthing, Tyler Hesser, Peter K. Kitanidis, Eric F. Darve

Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements.

Management Uncertainty Quantification

Deep learning-based fast solver of the shallow water equations

no code implementations23 Nov 2021 Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing, Tyler Hesser, Peter K. Kitanidis, Eric F. Darve

Furthermore, we augment the bathymetry posterior distribution to a more general class of distributions before providing them as inputs to ML algorithm in the second stage.


Routing algorithms as tools for integrating social distancing with emergency evacuation

no code implementations5 Mar 2021 Yi-Lin Tsai, Chetanya Rastogi, Peter K. Kitanidis, Christopher B. Field

One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation.

reinforcement-learning Reinforcement Learning (RL)

Application of deep learning to large scale riverine flow velocity estimation

1 code implementation4 Dec 2020 Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing, Tyler Hesser, Peter K. Kitanidis, Eric F. Darve

First, using the principal component geostatistical approach (PCGA) we estimate the probability density function of the bathymetry from flow velocity measurements, and then we use multiple machine learning algorithms to obtain a fast solver of the SWEs, given augmented realizations from the posterior bathymetry distribution and the prescribed range of BCs.


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