amamalak

Assistant Professor at University of Virginia

@UVA

Pinned Repositories

ats655-coursematerial
Course material for ATS 655: Objective Analysis with Prof. Elizabeth Barnes, Dept. of Atmospheric Science, Colorado State University.
Language:Jupyter Notebook1 0 00
CONUS_seasonal_precip_predictability_MatLab_Code-
Seasonal prediction of winter precipitation totals across CONUS using copula models and climate indices.
Language:MATLAB2 1 00
github-slideshow
A robot powered training repository :robot:
Language:Ruby0 1 10
Neural-Network-Attribution-Benchmark-for-Regression
Language:Jupyter Notebook2 2 01
Quantify_SAI_impacts
Language:Jupyter Notebook0 1 00
XAI-baselines
Language:Jupyter Notebook1 1 00
XAI_Fidelity_Assessment_CNN_GEO
Language:Jupyter Notebook1 1 02
actm-sai-csu
AI to detect, attribute, and quantify solar radiation management (SRM) effects and risks under a range of geopolitical scenarios. Project funded by DARPA‐PA‐21‐04‐02.
Language:Python6 3 01

amamalak/CONUS_seasonal_precip_predictability_MatLab_Code-
Seasonal prediction of winter precipitation totals across CONUS using copula models and climate indices.
Language:MATLAB2 1 00
amamalak/Neural-Network-Attribution-Benchmark-for-Regression
Language:Jupyter Notebook2 2 01
amamalak/ats655-coursematerial
Course material for ATS 655: Objective Analysis with Prof. Elizabeth Barnes, Dept. of Atmospheric Science, Colorado State University.
Language:Jupyter Notebook1 0 00
amamalak/XAI-baselines
Language:Jupyter Notebook1 1 00
amamalak/XAI_Fidelity_Assessment_CNN_GEO
Language:Jupyter Notebook1 1 02
amamalak/github-slideshow
A robot powered training repository :robot:
Language:Ruby0 1 10
amamalak/Quantify_SAI_impacts
Language:Jupyter Notebook0 1 00