Luis Antunes @_lantunes
Software Developer and Scientist. Interested in Computation, Complex Systems, Machine Learning and Chemistry. PhD. github.com/lantunes Toronto Joined November 2012-
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Dream up a brand-new material in 30 seconds, no PhD required. What once required years of training and expensive lab equipment now happens with a text prompt. CrystaLLM from @_lantunes and collaborators just transformed Ouro into every citizen scientist's materials lab. Simply…
Big shoutout and heartfelt appreciation to the team behind CrystaLLM. I tried the web application, and the results are awesome. 👏
Big shoutout and heartfelt appreciation to the team behind CrystaLLM. I tried the web application, and the results are awesome. 👏
CrystaLLM source code, weights and datasets have been released! We've also updated the preprint with benchmarking results, an SI, & more. Code: github.com/lantunes/Cryst… Preprint: arxiv.org/abs/2307.04340 In collaboration with @keeeto2000 & @rgraucrespo
Want to know how the latest large language models might help to generate new materials? Luis developed a great new method, Crystallm and has written an equally great and accessible blog on how it works:
Want to know how the latest large language models might help to generate new materials? Luis developed a great new method, Crystallm and has written an equally great and accessible blog on how it works:
Great blog post by @_lantunes about his CrystaLLM large language model for crystal structures crystallm.com. Now with API available for high-throughput use.
Great blog post by @_lantunes about his CrystaLLM large language model for crystal structures crystallm.com. Now with API available for high-throughput use.
Can LLMs be used to generate plausible crystal structures? Read an accessible overview of CrystaLLM, a generative model of crystal structures: blog.materialis.ai/crystal-struct…. In collaboration with @keeeto2000 & @rgraucrespo
Luis Antunes, @_lantunes, a PhD student at the Chemistry Department of @UniofReading has developed a "chatGPT-like" large language model for crystal structures. The AI model generates detailed crystal structures given a chemical composition.
Luis Antunes, @_lantunes, a PhD student at the Chemistry Department of @UniofReading has developed a "chatGPT-like" large language model for crystal structures. The AI model generates detailed crystal structures given a chemical composition.
📢 We're thrilled to present @_lantunes’s latest work in the pre-print "Crystal Structure Generation with Autoregressive Large Language Modeling" arxiv.org/abs/2307.04340. Work in collaboration with @keeeto2000. #compchem 1/3
Can we predict thermoelectric transport properties from composition? Read an accessible overview of our recent work on this topic: blog.materialis.ai/predicting-the…. Test the model yourself: thermopower.materialis.ai. In collaboration with @keeeto2000 & @rgraucrespo
Great new work by @keeeto2000 @rgraucrespo @_lantunes @UniRdg_Chem @QMULSEMS - 'Predicting #thermoelectric transport properties from composition with attention-based #deeplearning' - bit.ly/3ZMqB5s #machinelearning #materials #AI #energy #openscience #datascience #HPC
Our paper using attention-based #MachineLearning models (with #Transformer architecture like in #ChatGPT) to predict #thermoelectric behavior of hypothetical materials from composition, is out @MLSTjournal: tinyurl.com/2s4tx47. Led by @_lantunes in collab w/ @keeeto2000.
The latest version of CellPyLib supports Block Cellular Automata, which appear often in @stephen_wolfram's recent series on The Second Law. Learn more here: cellpylib.org/block_ca.html.
Can you tell a good #thermoelectric materials by its composition? @_lantunes shows what is possible, using #machinelearning, in this preprint: arxiv.org/abs/2212.06444. Collab with @keeeto2000 #compchem
Luis writes blogs as well as he writes code - if you want a nice accessible overview to our paper: nature.com/articles/s4152… this is a great place to start!
Luis writes blogs as well as he writes code - if you want a nice accessible overview to our paper: nature.com/articles/s4152… this is a great place to start! https://t.co/DAD55TWedy
Learn about distributed representations in #MachineLearning, why they matter in #compchem and materials science, and what SkipAtom is, in this superbly written post by @_lantunes. blog.materialis.ai/distributed-re…
Read here our review of #MachineLearning for investigating #thermoelectric materials. With @_lantunes, @vedviki, Jose Plata(@NewMaterialsLab), AV Powell (@UniRdg_Chem), and @keeeto2000. #compchem pubs.acs.org/doi/10.1021/bk…
@_lantunes developed a new representation for atoms, it's easy to use and makes most materials ML models more performant. He also made a really nice repo with it available via pypi github.com/lantunes/skipa…
@_lantunes developed a new representation for atoms, it's easy to use and makes most materials ML models more performant. He also made a really nice repo with it available via pypi github.com/lantunes/skipa…
Check out @_lantunes's SkipAtom paper, just out in @Nature_NPJ Computational Materials: Distributed representations of atoms and materials for #MachineLearning: nature.com/articles/s4152… #compchem. With @keeeto2000.
Evoloops and SDSR Loops are #CellularAutomata that reproduce and evolve, introduced by @HirokiSayama. Have a look at cellpylib.org/sdsr_evoloop.h… and the CellPyLib project to learn more! #ArtificialLife #Complexity
Just published in #JOSS_theOJ: 'CellPyLib: A Python Library for working with Cellular Automata' doi.org/10.21105/joss.…
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