Moritz R. Schäfer

Replication Data for: Enhanced Representation-Based Sampling for the Efficient Generation of Data Sets for Machine-Learned Interatomic Potentials

Moritz R. Schäfer, Johannes Kästner

This repository contains the data for our paper on "Enhanced Representation-Based Sampling for the Efficient Generation of Data Sets for Machine-Learned Interatomic Potentials". This includes both the simulation results as well as workflows and input files needed to recreate the results. Different …

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Replication Data for: How to Train a Shallow Ensemble

Moritz R. Schäfer, Matthias Kellner, Johannes Kästner, Michele Ceriotti

This repository accompanies our paper on "How to Train a Shallow Ensemble". It includes workflows and input files needed to reproduce the results. Most of the experiments are contained in the directory "0_convergence_nll_training". There is a separate directory for the experiments performed …

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apax-hub/apax: v0.14.0

Moritz R. Schäfer, Nico Segreto, Fabian Zills, Tobias M. Dijkhuis et autres

What's Changed [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/apax-hub/apax/pull/534 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/apax-hub/apax/pull/539 Include other activation functions by @TobiasDijkhuis in https://github.com/apax-hub/apax/pull/538 added zntrack.nodes entrypoint by @PythonFZ in https://github.com/apax-hub/apax/pull/542 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/apax-hub/apax/pull/540 3x3 nll loss by …

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apax-hub/apax: v0.14.0

Moritz R. Schäfer, Nico Segreto, Fabian Zills, Tobias M. Dijkhuis et autres

What's Changed [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/apax-hub/apax/pull/534 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/apax-hub/apax/pull/539 Include other activation functions by @TobiasDijkhuis in https://github.com/apax-hub/apax/pull/538 added zntrack.nodes entrypoint by @PythonFZ in https://github.com/apax-hub/apax/pull/542 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/apax-hub/apax/pull/540 3x3 nll loss by …

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apax-hub/apax: v0.13.1

Moritz R. Schäfer, Nico Segreto, Fabian Zills, Tobias Dijkhuis et autres

Fixed the optional import of optuna. What's Changed optuna run time import, bump version by @M-R-Schaefer in https://github.com/apax-hub/apax/pull/531 Full Changelog: https://github.com/apax-hub/apax/compare/v0.13.0...v0.13.1

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apax-hub/apax: v0.13.0

Moritz R. Schäfer, Nico Segreto, Fabian Zills, Tobias M. Dijkhuis et autres

What's Changed bump version from 0.12.3 to 0.12.4 by @PythonFZ in https://github.com/apax-hub/apax/pull/483 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/apax-hub/apax/pull/486 added per atom metrics by @Tetracarbonylnickel in https://github.com/apax-hub/apax/pull/484 Fix data pipeline for additional properties by @M-R-Schaefer in https://github.com/apax-hub/apax/pull/487 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] …

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Enhanced Representation-Based Sampling for the Efficient Generation of Data Sets for Machine-Learned Interatomic Potentials

Moritz R. Schäfer, Johannes Kästner

trajectories simulated with uncertainty-driven dynamics and ERBS and find that the latter significantly increases the exploration of configurational space.

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Enhanced Representation-Based Sampling for the Efficient Generation of Datasets for Machine-Learned Interatomic Potentials

Moritz R. Schäfer, Johannes Kästner

In this work, we present Enhanced Representation-Based Sampling (ERBS), a novel enhanced sampling method designed to generate structurally diverse training datasets for machine-learned interatomic potentials. ERBS automatically identifies collective variables by dimensionality reduction of atomic descriptors and applies a bias potential inspired …

bfcluster: Buttler-Fickel Distance and R2 for Mixed-Scale Cluster Analysis

Moritz R. Schäfer

Implements the distance measure for mixed-scale variables proposed by Buttler and Fickel (1995), based on normalized mean pairwise distances (Gini mean difference), and an R2 statistic to assess clustering quality.

Apax: A Flexible and Performant Framework for the Development of Machine-Learned Interatomic Potentials

Moritz R. Schäfer, Nico Segreto, Fabian Zills, Christian Holm et autres

We introduce Atomistic learned potentials in JAX ( apax ), a flexible and efficient open source software package for training and inference of machine-learned interatomic potentials. Built on the JAX framework, apax supports GPU acceleration and implements flexible model abstractions for fast …

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Replication Data for: Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials

Moritz R. Schäfer, Nico Segreto, Fabian Zills, Christian Holm et autres

This repository contains the data for our paper on "Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials". This includes both the simulation results as well as workflows and input files needed to recreate the results. Different experiments …

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Origin of Stereoselectivity in Ring Opening Metathesis Polymerization with Cationic Molybdenum Imido Alkylidene CAAC Complexes

Koushani Kundu, S. Haid, Moritz R. Schäfer, Wolfgang Frey et autres

Stereoselective ring opening metathesis polymerization (ROMP) of enantiomerically pure 2,3-dicarbomethoxynorborn-5-ene ((+)-DCMNBE) was accomplished by the action of cationic tetra- and pentacoordinated molybdenum imido alkylidene cyclic alkyl amino carbene (CAAC) complexes that are chiral at molybdenum. The same catalysts were also utilized to …

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