Markus J. Buehler
Orcid: 0000-0002-4173-9659
According to our database1,
Markus J. Buehler
authored at least 36 papers
between 2004 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Generative Artificial Intelligence Extracts Structure-Function Relationships from Plants for New Materials.
CoRR, August, 2025
AutomataGPT: Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata.
CoRR, June, 2025
Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles.
CoRR, April, 2025
Self-Organizing Graph Reasoning Evolves into a Critical State for Continuous Discovery Through Structural-Semantic Dynamics.
CoRR, March, 2025
CoRR, February, 2025
Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model.
CoRR, February, 2025
CoRR, January, 2025
CoRR, January, 2025
Towards Agentic AI for Science Hypothesis Generation, Comprehension, Quantification, and Validation.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025
2024
Accelerating scientific discovery with generative knowledge extraction, graph-based representation, and multimodal intelligent graph reasoning.
Mach. Learn. Sci. Technol., 2024
Learning the rules of peptide self-assembly through data mining with large language models.
CoRR, 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
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
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
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
IEEE Trans. Control. Syst. Technol., 2004