A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.
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Updated
Jun 8, 2023 - Python
A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.
Scale down Kubernetes deployments after work hours
Code repository associated with "Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification" (Getter, Bessac, Rudi, Feng).
Using Stereo SGM to calculate the disparity map of two images :Stereo Processing by Semiglobal Matching and Mutual Information .
Analyzer that shows why your Kubenetes cluster does not scale down like you expect
Bayesian Network-Infored Conditional Random Forests
Scripts that I've used during grad school for data collection, analysis, visualization, cleaning, wrangling, etc., for classes, project reports, and manuscripts.
Diffusion for climate downscaling
Based on the code of Daliakopoulos I.N., Katsanevakis, S., and Moustakas, A.
Ease the use of the climate4r package to downscale TraCE21ka and CMIP5 climate data in combination with UERRA reanalysis data.
Multi-Fidelity Gaussian Processes (MFGP) applied to downscaling sparse climatic data.
Created algorithm in C to detect and highlight best image match with template (2 px accuracy) using pixelwise brute force. The algorithm is optimized by 16x to take less than 5 seconds per image-template pair on i7 processor by down-sampling.
Multicore! Faster!
Python package to reconstruct and extend observational climate series through empricial downscaling of large-scale models
Cost saving K8s controller to scale down and up of resources during non-business hours
Awesome-AI4Earth: a curated list of machine learning in Earth System, especially for weather and climate.
Python tool for downsizing Microsoft PowerPoint presentations (pptx) files.
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