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## Goal
* to be able to run a full simulatoin using a machine-learned potential
* The descriptor calculation and ML model evaluation shoudl happen direclty from the C++ core, to obtain good scaleabil…
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### Email (Optional)
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### Problem
Some of the workflows / tasks defined in matcalc and atomate2 for ML interatomic potentials are nearly identical. Part of this is because the initial …
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How can we best support parallelization of ML potentials across GPUs?
We're dealing with models that are small enough to be replicated on each GPU, and only O(N) data (positions, box vectors) needs…
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Very nice plugin! Would you be interested in exposing it through [OpenMM-ML](https://github.com/openmm/openmm-ml)? It provides a standard interface for creating simulations with ML potentials. You …
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Here are the discussion topics suggested for this year's workshop. We will cycle through them throughout the week:
- Trajectories
- Collections + providing data for training ML potentials
- Prope…
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Hi,
I'm working on implementing buffered force mixing (https://pubs.acs.org/doi/10.1021/jp405974b) in openMM, where the use case would be having an ML potential compute forces on a subset of the sy…
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Greetings,
I'm Marco Ravalli, a phD student working on molecular dynamics by classical interatomic potentials. I'm currently trying to use one of the pretrained MACE models to work with my systems, …
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- [x] Add category
- [x] Update category:
**Category details:**
Currently, the distribution of projects among categories is very uneven.
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Active learning 4 projects
Bio…
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This thread is intended to collect some concrete use cases for adding first-class support for quantum machine learning (QML) use cases.
We have identified several classes of use cases we would lik…
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Unconference Federated Learning
# Title
Cases and applications of federated learning
# Description
Centralized Learning (CL) in Machine Learning refers to the traditional approach where all d…