ahtloor Goto Github PK

active_motif_orr

active motif based screening to discover active, selective and stable ORR catalysts for H2O2 production

ahtloor

Config files for my GitHub profile.

ai-deadlines

:alarm_clock: AI conference deadline countdowns

al_mlp

Active Learning for Machine Learning Potentials

amptorch

AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch

catalyst-acquisitions

Acquisition functions for density function theory (DFT) simulations for catalyst screening

catalystsre

catkit

General purpose tools for high-throughput catalysis

catmap

Catalyst Micro-kinetic Analysis Package for automated creation of micro-kinetic models used in catalyst screening

cgcnn

Crystal graph convolutional neural networks for predicting material properties.

cleavage_energy_manuscript

cluster_mlp

A Genetic algorithm + active learning framework to identify the optimal metallic nanoclusters for a given number of atoms

cp2k

Quantum chemistry and solid state physics software package

doeionomers

dogss

flamyngo

Flask frontend for MongoDB

gaspy

gaspy_feedback

This is a GASpy submodule that is meant to work with GASpy_regressions to determine what GASpy simulations to run next.

gaspy_regressions

Regressions performed on databases created by GASpy. It is intended to be used as a submodule of GASpy.

magpie_python

Python version of magpie attribute generators.

math-methods-chemical-engineering

Course notes for the CMU course 06-262 Math Methods of Chemical Engineering (ODE's, linear algebra, PDEs, stats) in the form of jupyter notebooks

mixedmetaloxides

mtt-md

Molecular Thermodynamic Theory with MD simulations

nuclearitycalculation

Functions for surface nuclearity calculations given an Atoms object for a slab.

offlineal-for-mlps-manuscript

Physics Enabled Convergence of Offline Active Learning with Machine Learning Potentials

open-catalyst-dataset

Workflow for creating and analyzing the Open Catalyst Dataset

s19-06262

numerical notes for 06-262 at CMU (spring 19)

sella

uncertainty_benchmarking

Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.