Calibration of a wind erosion model using remote sensing-derived vegetation characteristics
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Updated
Sep 21, 2022 - Jupyter Notebook
Calibration of a wind erosion model using remote sensing-derived vegetation characteristics
In this problem statement, a sequence of genetic mutations and clinical evidences, i.e. descriptive texts as recorded by domain experts are used to classify the mutations to conclusive categories, to be used for diagnosis of the patient.
We address the calibration of SEIR-like epidemiological models from daily reports of COVID-19 infections in New York City, during the period 01-Mar-2020 to 22-Aug-2020. Our models account for different types of disease severity, age range, sex and spatial distribution. The manuscript related to such simulations can be found in https://arxiv.org/…
Calibration of the significant Social Force Parameters in Vissim
In this project, I analyze, plot and clean Tanzania's Water Pump Dataset, which is provided by DrivenData.org for a competition.
This is the official PyTorch codebase for the ACL 2023 paper: "What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization".
An R package to produce standard graphs for HEC-RAS models.
Parameter space reduction algorithm for search-based model calibration algorithms
Interface to auto-calibration software UCODE (https://igwmc.mines.edu/ucode/)
This instruction aims to reproduce the results in the paper “Calibration of inexact computer models with heteroscedastic errors” proposed by Sung, Barber, and Walker (2022).
Data for the Quantitative Single-Neuron Modeling Competition (2007).
Code for calibration as a method of design.
This R package allows calibration parameter estimation for inexact computer models with heteroscedastic errors proposed by Sung, Barber, and Walker (2022) in SIAM/ASA Journal on Uncertainty Quantification.
Data for the Quantitative Single-Neuron Modeling Competition (2009).
Paper: Computer model calibration as a method for design
GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga
An application of NLP and classical ML algorithms to an interesting real-world use case of predicting similarity between two questions on Quora. This allows the platform to combine similar questions into one and combine their answers to avoid duplication and unnecessary confusion.
[MICCAI2022] Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores.
ARBO is a package for simulation and analysis of arbovirus nonlinear dynamics.
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