lcmd-epfl Goto Github PK
Name: Laboratory for Computational Molecular Design
Type: Organization
Location: Lausanne
Blog: https://lcmd.epfl.ch/
Name: Laboratory for Computational Molecular Design
Type: Organization
Location: Lausanne
Blog: https://lcmd.epfl.ch/
Code to support the paper: S. Vela, A. Fabrizio, K. R. Briling, and C. Corminboeuf, “Machine-Learning the Transition Density of the Productive Excited States of Azo-dyes”, J. Phys. Chem. Lett. 2021, 5957–5962.
B2R2 Reaction Representation
Benchmarking reaction representations for the learning of reaction barriers
Energy Profile Similarity Maps
Fragment decomposition analysis tool for electronic coupling in charge transfer process of organic semiconductors
Machine learning models for the FORMED database and downstream tasks.
Introduction to QML representations, both how they are constructed and how to generate them using the qmlcode.
Introductory tutorial explaining how to train and use Behler-Parrinello NNPs in advanced molecular dynamics of complex systems
A program to automatically perform microkinetic modeling and generate microkinetic volcano plots for homogeneous catalysis reactions using energy data.
Code for the Metric Learning for Kernel Ridge Regression algorithm
Python scripts for MLR regression fitting accompanying the paper "Harvesting the Fragment-Based Nature of Bifunctional Organocatalysts to Enhance Their Activity".
Using the Molassembler python API to generate an ensemble of TS guesses from a template.
Python script to create a web app with Dash to visualize molecular data and molecular geometries
Modular Replica Exchange Simulator
A platform for catalyst discovery
A flexible Genetic Algorithm Optimizer for the NaviCat project.
Code to support the paper: A. Fabrizio, K. R. Briling, D. D. Girardier, and C. Corminboeuf, “Learning on-top: regressing the on-top pair density for real-space visualization of electron correlation”, J. Chem. Phys. 153, 204111 (2020)
Stack of codes for dedicated pre- and post-processing tasks for Quantum Machine Learning (QML)
Code to accompany the reply to comment on "Physics-based representations for machine learning properties of chemical reactions".
Code to support the paper: A. Fabrizio, A. Grisafi, B. Meyer, M. Ceriotti, and C. Corminboeuf, “Electron density learning of non-covalent systems”, Chem. Sci. 10, 9492 (2019)
Code to support the paper: A. Fabrizio, K. R. Briling, and C. Corminboeuf, “SPAHM: the Spectrum of Approximated Hamiltonian Matrices representations”, Digital Discovery, 2022, 1, 286–294
A tools-barebone setting of cell2mol fro the materialscoud.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.