9 citations · 42 across the 16 of their papers we have counts for
7 papers · 1 filter
Rapid and Automated Alloy Design with Graph Neural Network-Powered LLM-Driven Multi-Agent Systems
Alireza Ghafarollahi, Markus J. Buehler
A multi-agent AI model is used to automate the discovery of new metallic alloys, integrating multimodal data and external knowledge including insights from physics via atomistic si…
LifeGPT: Topology-Agnostic Generative Pretrained Transformer Model for Cellular Automata
Jaime A. Berkovich, Markus J. Buehler
Conway's Game of Life (Life), a well known algorithm within the broader class of cellular automata (CA), exhibits complex emergent dynamics, with extreme sensitivity to initial con…
SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning
Alireza Ghafarollahi, Markus J. Buehler
A key challenge in artificial intelligence is the creation of systems capable of autonomously advancing scientific understanding by exploring novel domains, identifying complex pat…
Multicell-Fold: geometric learning in folding multicellular life
Haiqian Yang, Anh Q. Nguyen, Dapeng Bi +2
During developmental processes such as embryogenesis, how a group of cells fold into specific structures, is a central question in biology that defines how living organisms form. E…
AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence
Alireza Ghafarollahi, Markus J. Buehler
The design of alloys is a multi-scale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting exp…
X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design
Eric L. Buehler, Markus J. Buehler
We report a mixture of expert strategy to create fine-tuned large language models using a deep layer-wise token-level approach based on low-rank adaptation (LoRA). Starting with a…
ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learning
A. Ghafarollahi, M. J. Buehler
Designing de novo proteins beyond those found in nature holds significant promise for advancements in both scientific and engineering applications. Current methodologies for protei…