Markus J. Buehler

Orcid: 0000-0002-4173-9659

According to our database1, Markus J. Buehler authored at least 26 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
Accelerating scientific discovery with generative knowledge extraction, graph-based representation, and multimodal intelligent graph reasoning.
Mach. Learn. Sci. Technol., 2024

Rapid and Automated Alloy Design with Graph Neural Network-Powered LLM-Driven Multi-Agent Systems.
CoRR, 2024

PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinking.
CoRR, 2024

LifeGPT: Topology-Agnostic Generative Pretrained Transformer Model for Cellular Automata.
CoRR, 2024

SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning.
CoRR, 2024

Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities.
CoRR, 2024

AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence.
CoRR, 2024

Multicell-Fold: geometric learning in folding multicellular life.
CoRR, 2024

Cephalo: Multi-Modal Vision-Language Models for Bio-Inspired Materials Analysis and Design.
CoRR, 2024

X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Design.
CoRR, 2024

ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learning.
CoRR, 2024

Learning Dynamics from Multicellular Graphs with Deep Neural Networks.
CoRR, 2024

2023
Unsupervised cross-domain translation via deep learning and adversarial attention neural networks and application to music-inspired protein designs.
Patterns, March, 2023

MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledge.
CoRR, 2023

Generative retrieval-augmented ontologic graph and multi-agent strategies for interpretive large language model-based materials design.
CoRR, 2023

ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a protein language diffusion model.
CoRR, 2023

MechGPT, a language-based strategy for mechanics and materials modeling that connects knowledge across scales, disciplines and modalities.
CoRR, 2023

Generative modeling, design and analysis of spider silk protein sequences for enhanced mechanical properties.
CoRR, 2023

BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-inspired Materials.
CoRR, 2023

MeLM, a generative pretrained language modeling framework that solves forward and inverse mechanics problems.
CoRR, 2023

Generative Pretrained Autoregressive Transformer Graph Neural Network applied to the Analysis and Discovery of Novel Proteins.
CoRR, 2023

Modeling and design of heterogeneous hierarchical bioinspired spider web structures using generative deep learning and additive manufacturing.
CoRR, 2023

Diatom-inspired architected materials using language-based deep learning: Perception, transformation and manufacturing.
CoRR, 2023

2022
Interactive exploration of a hierarchical spider web structure with sound.
J. Multimodal User Interfaces, 2022

2020
Sonification of a 3-D Spider Web and Reconstitution for Musical Composition Using Granular Synthesis.
Comput. Music. J., 2020

2004
Optimal sensor design and control of piezoelectric laminate beams.
IEEE Trans. Control. Syst. Technol., 2004


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