• Stars
    star
    2
  • Language
    Jupyter Notebook
  • License
    GNU Lesser Genera...
  • Created about 7 years ago
  • Updated over 4 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

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

More Repositories

1

GASpy

Python
60
star
2

amptorch

AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch
C++
59
star
3

vasp-interactive

Jupyter Notebook
52
star
4

finetuna

Active Learning for Machine Learning Potentials
Python
42
star
5

uncertainty_benchmarking

Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.
Jupyter Notebook
37
star
6

wherewulff

WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions
Python
24
star
7

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
Jupyter Notebook
20
star
8

GASpy_manuscript

Jupyter Notebook
12
star
9

catgym

Surface segregation using Deep Reinforcement Learning
Python
11
star
10

charge-density-models

Python
9
star
11

Cleavage_Energy_Manuscript

Jupyter Notebook
7
star
12

ml_catalysis_tutorials

Jupyter Notebook
6
star
13

cluster_mlp

A Genetic algorithm + active learning framework to identify the optimal metallic nanoclusters for a given number of atoms
Jupyter Notebook
6
star
14

F22-06-325

Jupyter Notebook
6
star
15

tmQM_wB97MV

Code for "Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Dataset"
Jupyter Notebook
5
star
16

catlas

files for dask parallelization of OCP energy predictions.
Python
4
star
17

espresso_tools

The Quantum Simulation Group (QSG) at Lawrence Livermore National Lab (LLNL) has developed various tools to manage their [Quatum Espresso](https://www.quantum-espresso.org/) calculations. The Ulissi group has ported, open-sourced, and managed these tools to Github on their behalf.
Python
3
star
18

OfflineAL-for-MLPs-manuscript

Physics Enabled Convergence of Offline Active Learning with Machine Learning Potentials
Jupyter Notebook
2
star
19

s19-06262

numerical notes for 06-262 at CMU (spring 19)
Jupyter Notebook
2
star
20

active_motif_ORR

active motif based screening to discover active, selective and stable ORR catalysts for H2O2 production
Jupyter Notebook
1
star
21

catalyst-acquisitions

Acquisition functions for density function theory (DFT) simulations for catalyst screening
Jupyter Notebook
1
star
22

DOE_HER

Jupyter Notebook
1
star
23

nitrate

Repository for tools and code for water purification (NO3 RR)
Jupyter Notebook
1
star
24

Open-Catalyst-Dataset

Workflow for creating and analyzing the Open Catalyst Dataset
Python
1
star