Machine Learning: Science and Technology
@MLSTjournal
A multidisciplinary, #openaccess journal devoted to the application and development of #machinelearning for the sciences. Published by @IOPPublishing.
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We are now on Bluesky! Follow our account @iopp-mlresearch.bsky.social on Bluesky for more #MachineLearning and #AI research
From Thursday, 5 June, X will no longer be our primary platform for sharing news. We would love to connect with you on: 🦋 Bluesky - bsky.app/profile/ioppub… LinkedIn - linkedin.com/company/iop-pu… Facebook - facebook.com/ioppublishing/ Threads - threads.net/@iop.publishing
Our paper is now out in @MLSTjournal, the BEST place for stat mech for ML! Response theory of first passage processes and the quasi-steady-state hypothesis helps optimize training protocols for neural nets👇@chemistrytau @BioSoftTAU @TelAvivUni doi.org/10.1088/2632-2…
My video interview with @QuantaMagazine about AI-designed physics experiments, AI as a Muse for new ideas in Science, and Artificial Scientists: youtube.com/watch?v=T_2ZoM…
youtube.com
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How the 'Artificial Scientist' Lab Creates Experimental Designs
We show how to estimate the impact of research ideas before they were even born -- just published in @MLSTjournal [paper] iopscience.iop.org/article/10.108… [GitHub]: github.com/artificial-sci… spearheaded by @GuXuemei Important for future artificial muses, to generate impactful new ideas.
Our LLM4Mat-Bench paper is now published @MLSTjournal ✨ Test your favorite LLM on the benchmark to predict material properties. 📖Paper: iopscience.iop.org/article/10.108… 💻Code: github.com/vertaix/LLM4Ma…
#NewPaper Have you been wondering how your favorite LLM, e.g. Llama, Mistral, or Gemma performs on materials property prediction? We have just released LLM4Mat-Bench, an extensive benchmark for materials property prediction with LLMs! LLM4Mat-Bench has unique features: ☀️It…
Congratulations to all recipients of our Outstanding Reviewer Awards! 🎉Your commitment, timeliness, quality, & quantity of reports is celebrated across our journals. Let's celebrate all #PeerReview contributions that uphold #ResearchIntegrity Discover 👉 ow.ly/tb9850VkHNn
📜Our new paper on detecting quantum vortices with Convolutional Neural Networks has been published in @MLSTjournal! ✅The scheme offers efficient, system-wide vortex detection - even in noisy, experimental data. 🔗 Read here: iopscience.iop.org/article/10.108… #MachineLearning
Physics and AI: A powerful duo expanding our understanding of the Universe! Join our workshop at AI UK 2025, The Alan Turing Institute, to explore how physics can tackle AI's biggest challenges. In-person delegate booking opens 10am on March 12th: ai-uk.turing.ac.uk/programme-2025/ #Turing
Paper alert! "New gravitational wave discoveries enabled by machine learning", A. Koloniari, E. Koursoumpa, P. Nousi, P. Lampropoulos, N. Passalis, A. Tefas, N. Stergioulas, doi.org/10.1088/2632-2… μέσω @MLSTjournal (Open Access)
📣Join us on April 27, for the "AI-driven discoveries: Machine Learning for the Physical Sciences" workshop. This international event will bring together top researchers to discuss the role of #AI and machine learning in advancing physical sciences. ow.ly/iLsf50V2Kvk #AI
✨Become an IOP Peer Review Excellence graduate this month! With more than 4,300 researchers already signed up to our free and rigorously assessed online course, come and take a look today - ow.ly/Hi0450V0ePT #EarlyCareerResearcher #PhysicalScience #PeerReview
New paper alert. "Stochastic black-box optimization using multifidelity score function estimator," published in @MLSTjournal (@IOPPublishing ) w\ @mandrakeMojito @SKoutsourelakis prof. Hans Bungartz. iopscience.iop.org/article/10.108… #BlackBoxOptimization #SciML #UQ #ML
👋 Are you an #EarlyCareerResearcher looking to gain #PeerReview experience, or an experienced supervisor eager to support the next generation? We've got you covered! Find out more 👇 ow.ly/QPWY50UOAnS
Our new research article on "Characterizing out-of-distribution generalization of neural networks: application to the disordered SSH model" published in @MLSTjournal by our great student @KacperCybinski led by Prof. A. Dawid @MolecularRobot with @ICFOnians doi.org/10.1088/2632-2…
I’m pretty excited about our new paper, which is a follow up to our last paper using AI to help solve a problem in theoretical particle physics. (With Lance, @f_charton, Matthias, Tianji, and @merz_garrett
Link to paper: arxiv.org/abs/2501.05743 Previous AI/ML paper in @MLSTjournal : iopscience.iop.org/article/10.108…
AI predicts that most of the world will warm much faster than previously predicted, according to a new study published today in @ERLjournal. ⏰ Find out more: ow.ly/iSNk50Uo4bL
🦾Discover what our new journal 'Machine Learning: Engineering' contributes to the #MachineLearning and #AI landscape! Our Editor-in-Chief shares key insights about our exciting new journal which is now open for submissions! ow.ly/7hf050Ulu80
Read the full article in @MLSTjournal at iopscience.iop.org/article/10.108…
Quantum multitasking? When a quantum computer processes data, it must translate it into understandable quantum data. A team led by @Tohoku_Univ has created an #algorithm capable of optimizing multiple targets at once in quantum compilation. @MLSTjournal #computing #technology
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