uw-cmg Goto Github PK

asr_model

Random forest model for predicting stability and T-dependent area specific resistance of perovskite catalysts

atomgame3d

3D port of game prototypes

atomtouch

AtomTouch: App for Interactive Exploration of the Nanoworld

atomtouchprototypes

camd

Agent-based sequential learning software for materials discovery

cmg_example_model_predictions

All models created by the Computational Materials Group (CMG) at the University of Wisconsin-Madison (UW-Madison) will reside here.

defect-detection

Loop defect detection project with deep learning framework

defectstemvideoanalysis

Defect STEM Video Analysis

diffusion_model

gan-stem-conv2multislice

mast

MAterials Simulation Toolkit for use with pymatgen

mast-ml

MAterials Simulation Toolkit for Machine Learning (MAST-ML)

mast-sey

Monte Carlo Modeling of Secondary Electron Emission using fully DFT input

material_error_bar_predictions

Vidit's work on error bar predictions.

materials_application_domain_machine_learning

A package for definining the domain of a machine learning model via a feature dissimilarity metric.

matlab-loop-detection

medicalimganalysis-bleedingsitesdetection

Medical Image Analysis Project

meghanpanccystmachine

Codes for machine learning of Panccyst Cancer

ml-error

ml4xrayspecklepattern

Codes for Machine learning for interpreting coherent X-ray speckle patterns

ml_bandgap

mns_cd

This is the Cluster Dynamics code for evolution of Mn-Ni-Si in low-Cu RPV steels

model_bandgap

Random forest model to predict the electronic bandgap of materials

model_concrete

Random forest model to predict the compressive strength of concrete mixtures

model_debyet_aflow

Random forest model to predict the Debye temperature of materials in the AFLOW database

model_dielectric

Random forest model to predict the dielectric constant of materials

model_diffusion

Random forest model to predict the dilute solute activation energy for diffusion

model_double_perovskite_gap

Random forest model to predict the bandgap of double perovskites

model_elastic_tensor

Random forest model to predict the bulk modulus of materials

model_exfoliatione

Random forest model to predict the exfoliation energy of materials