Materials Virtual Lab
The official Youtube Channel of the Materials Virtual Lab (http://www.materialsvirtuallab.org). an interdisciplinary group of scientists who aims to bring forth a data-driven future for materials science.
Insights into Solid Electrolytes from Long-time and Large-size Scale Simulations with MLIPs
MRS Fall 2023 Tutorial - ML and HT Discovery and Design of Next-Gen Materials for SSBs
NANOx81 Lecture 7 - Trees
NANO181/281 Lecture 5 - Extending Linear Methods
NANO181/281 Lecture 3 - Linear Methods
NANO181/281 Lecture 5 - Linear Classification
ACS Fall 2023 Keynote Talk - Machine Learning; Learning Humans
20230705 - NUS Seminar - Universal Machine Learning Models for Unconstrained Materials Design
243rd ECS Meeting - Machine Learning for Solid State Batteries: Progress vs Hype
NANO266 Lecture 11 - Modeling Transition States
NANO266 Lecture 10 - Surfaces and Interfaces
NANO266 Lecture 9 - Tools of the Modeling Trade
NANO266 Lecture 8 - Properties of Periodic Structures from Quantum Mechanics
NANO266 Lecture 7 - Quantum Mechanical Modeling of Periodic Structures
NANO266 Lecture 6 - Molecule properties from QM Modeling.pdf
NANO266 Lecture 5 - Exchange Correlation Functionals
NANO266 Lecture 3 - Beyond Hartree-Fock
NANO266 Lecture 4 - Introduction to DFT
NANO266 Lecture 2 - The Hartree Fock Approximation
NANO266 Lecture 1 - A Gentle Introduction into QM
MaterialsSquare Webinar - An "AlphaFold" for Materials Science
NANO181/281 Lecture 8 - Neural networks
NANO181/281 - Lecture 7 - Generalized Additive Models and Trees
Exploring the Matterverse with Graph Deep Learning
NANOx81 Lecture 6 - Kernel Methods
NANOx81 Lecture 5 - Unsupervised Learning
NANO181/281 Lecture 4 - Linear Methods for Classification
NANO181/281 Lecture 3 - Linear Methods
NANO181/281 Lecture 2 - Introduction to Data Science in Materials Science
NANO181/281 Lecture 1- Python for Data Science and Materials Science