Top Tweets for #mlip
Glad to share our new paper in ACS Catalysis, developed in collaboration with BASF. 🔬
📄 https://t.co/o09CAGXdaN
#Catalysis #MLIP #DFT #MachineLearning #HeterogeneousCatalysis #ACSCatalysis
Paper: https://t.co/0QhQOuRwNG
Code: https://t.co/hIE4UoyG7v
This work was made possible by an amazing team: @Dafidofff , @rishabh16_ , @SharvVadgama , @FrisodeKruiff, @Thijs, @RexYing, @ClarisaSanchez, @Georgbokman, and @erikjbekkers
#Transformers #Equivariance #MLIP
LiTEN-FF: An equivariant NN foundation model for biomolecular simulations.
Using linear tensorized attention to efficiently capture many-body interactions.
@NatureComms
#MLIP #MachineLearing #ForceField #quantumchem #EGNN #AIforScience #MolecularDynamics #DrugDiscovery
New preprint alert!🚨We introduce PROBE: a framework for uncertainty quantification in #machinelearning interatomic potentials (#MLIP). Instead of the typical regression approach, PROBE frames #uncertainty as a simple binary question: is this prediction reliable or not? This simplification makes the problem tractable, and we show that a lightweight classifier trained on top of a frozen MLIP's internal representations is all you need. Additionally, PROBE's attention mechanism produces per-atom importance maps highlighting exactly which atoms drove an unreliable prediction, at no extra cost. #comchem https://t.co/0elIuraUJL
Excited to share MolCryst-MLIPs — an open database of fine-tuned MLIPs for molecular crystals 🔬
9 validated potentials + full DFT datasets. More systems coming soon!
📄 https://t.co/CDGfH3ev1T
🗄️ https://t.co/CHAqRvXHZC
#CompChem #MLIP #MachineLearning
Amidst the #CCSC2026 posts, here’s a TBT #JournalClub from Gregor Lauter on the assessment of #MLIP for #GCMC gas adsorption in #framework materials by Jack Evans https://t.co/Na1A67fpFG
With some delay today is a #tbt of latest #JournalClub entries from our group. First off, understanding and evaluating #uncertainty in #MLIP by Dr. Clara Kirkvold https://t.co/Na1A67fpFG
機械学習ポテンシャル(MLIP)🧠が第一原理計算並みの精度と高速化をどう両立しているのかを解説。
アーキテクチャの進化、学習データの「質」の重要性、検証手法まで網羅。Matlantisが高精度ながら汎用性を持っているのかを、研究動向とあわせて紐解きます。
https://t.co/3pNyDzLNhE
#Matlantis #MLIP
📍City of Mbombela is changing the game in local health planning!
The 2023–2028 #MLIP is being developed through a new, interactive, recorded, multisectoral approach.
Tweet 2:
🗣️ “This time we’re doing things differently…” – Themba Ndaba
• Real-time engagement
📢For those still hanging out here, a new #cookbook recipe landed, demonstrating >2x speedup of *conservative* MD for the PET-MAD universal #MLIP using multiple time stepping. Check out the details at the other place, or head to https://t.co/f2ft2jmfpH #compchem #machinelearning
Extremely glad to share this novel @JAmCeramSoc @ACerSNews led by @assil_bzd, @firasshuaib @ircerteam on an AI-ML clustering approach for modeling glasses, with minimal data and #MLIP! It's always inspiring to collaborate with such talented people. 👉
Happy to share our @JAmCeramSoc work on AI-ML modeling of amorphous structures, led by @firasshuaib
We:1️⃣ Cluster structures using local&long-range descriptors 2️⃣ Fit MLIPs via active learning.
=> Minimal-size databases achieve MLIP with DFT accuracy!
https://t.co/i2Y3mybpOU
2024年5月22日に第26回理論化学討論会にて
”Matlantisが切り拓く新しい材料科学 －最新の機械学習力場と連携機能－”
というタイトルで講演させていただきました。下記URLより資料をご覧いただけます。
https://t.co/IpL5iFbAXY
#量子化学計算 #分子動力学 #マテリアルズインフォマティクス #MLIP
"Hi, I'm Christina and a #PostDoc at @BAMResearch in the junior group of @MolecularXtal. We are working on a Python-based workflow to automate machine-learned interatomic potential #MLIP fitting and all the related #DFT and benchmarking steps.
#BrainConf22 starts in 4 days! You can also find there our two recently published works. I will be happy to meet you there!
https://t.co/3MAkrymcgh
https://t.co/8GVaMiSFnW
https://t.co/ZYmarGlhnV
@Brain1878
#NeuroTwitter #Neurogenetics #TUBB4A #NMA #MLIP
Very proud to present our recent works on #TUBB4A and #MLIP at The Brain Conference later this month. Great achievement thanks to all the fantastic co-authors.
https://t.co/8GVaMiSFnW https://t.co/ZYmarGlhnV @FelixBenninger @BaselLina #Neurogenetics #Neurology #RareDisease #NMA
Very proud to present our recent works on #TUBB4A and #MLIP at The Brain Conference later this month. Great achievement thanks to all the fantastic co-authors.
https://t.co/8GVaMiSFnW https://t.co/ZYmarGlhnV @FelixBenninger @BaselLina #Neurogenetics #Neurology #RareDisease #NMA
REGISTER NOW!!
THE BRAIN CONFERENCE 24-25 Feb 2022
Don't worry if you are unable to make the event on the 24/25 Feb because all of the talks and content will be available to registrants for 2 months after the event
ONLY 3 WEEKS TO GO!!
Register here: https://t.co/en1Gi4JEhk
NOW >7000 DOWNLOADS! 'The #MLIP package: moment #tensor potentials with MPI and active learning' by @Alex_Shapeev et al @sk_en @skolkovo_ru @Skoltech @MSETUDELFT https://t.co/3rbaANJXx9 #tensornetworks #machinelearning #compchem #quantum #neuralnetworks #materials #DFT #bigdata
1st paper of 2022 just published in European Journal of Neurology @EANeurology reporting #RareDisease w/ myopathy, hyperCKemia & possible cardiac muscle involvement due to #MLIP loss of function. Great collaboration w/ Rabin Medical Center & @UofMaryland
https://t.co/itu3oKlzUT
Top 10 #mostread @MLSTjournal articles in 2021 - #5 with 6478 downloads! 'The #MLIP package: moment #tensor potentials with MPI and active....' by @Alex_Shapeev et al @sk_en @skolkovo_ru @Skoltech @Skoltech_ru https://t.co/3rbaANJXx9 #tensornetworks #machinelearning #compchem #AI
Another milestone:'The #MLIP package: moment #tensor potentials with MPI and active learning' by @Alex_Shapeev et al @sk_en @skolkovo_ru @Skoltech @Skoltech_ru now hits 6000 downloads! https://t.co/3rbaANJXx9 #tensornetworks #machinelearning #compchem #quantum #materials #DFT
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