Picture for Daniel Schwalbe-Koda

Daniel Schwalbe-Koda

Information theory unifies atomistic machine learning, uncertainty quantification, and materials thermodynamics

Add code
Apr 18, 2024
Viaarxiv icon

Inorganic synthesis-structure maps in zeolites with machine learning and crystallographic distances

Add code
Jul 20, 2023
Viaarxiv icon

Data efficiency and extrapolation trends in neural network interatomic potentials

Add code
Feb 12, 2023
Viaarxiv icon

Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials

Add code
Feb 01, 2021
Figure 1 for Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials
Figure 2 for Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials
Figure 3 for Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials
Figure 4 for Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials
Viaarxiv icon

Generative Models for Automatic Chemical Design

Add code
Jul 02, 2019
Figure 1 for Generative Models for Automatic Chemical Design
Figure 2 for Generative Models for Automatic Chemical Design
Figure 3 for Generative Models for Automatic Chemical Design
Figure 4 for Generative Models for Automatic Chemical Design
Viaarxiv icon