Workshops

Optimization and Search of Energy Landscapes by Evolutionary Algorithms and Data Mining

A multistart multisplit direct search methodology for global optimization

Scalable and efficient multicanonical algorithms for first-principles based Monte Carlo simulations

Systematic development of neural network-based interatomic models for structure prediction

Energy Landscapes: Structure, Dynamics, and Thermodynamics

Improving Atomistic Crystal Structure Prediction Searches through Symmetric Initialization

Machine learning and global optimization for materials discovery

Automatic search versus chemical rules in materials structure study

How to Escape Saddle Points Efficiently?

High-throughput experimentation and machine learning for materials discovery

Applications of machine learning to materials data

A meta-machine-learning method for identifying effective descriptors of materials properties

Local energy decomposition via machine learning

An Equal Space for Complex Data with Unknown Internal Order: Observability, Gauge Invariance and Manifold Learning

An Optimal Control Approach to Efficient Estimation of Rare Event Statistics

Structure Prediction of Molecular Crystals with GAtor and Genarris

Ensemble representation of surface-mounted cluster catalysts

Exploring discrete and continuous landscapes

Exploring the Small Molecule Conformer Problem

Human vs Machine: deciphering the structure of organic-inorganic interfaces

Surface Adsorbate Polymorph Prediction With Little Effort

ALAMO: Machine learning from data and first principles

Algorithmic Tools for Smooth Nonconvex Optimization