Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
Opportunities and challenges for machine learning-assisted enzyme engineering
Enzymes can be engineered at the level of their amino acid sequences to optimize key
properties such as expression, stability, substrate range, and catalytic efficiency─ or even to …
properties such as expression, stability, substrate range, and catalytic efficiency─ or even to …
Generalized biomolecular modeling and design with RoseTTAFold All-Atom
Deep-learning methods have revolutionized protein structure prediction and design but are
presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which …
presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which …
MeLM, a generative pretrained language modeling framework that solves forward and inverse mechanics problems
MJ Buehler - Journal of the Mechanics and Physics of Solids, 2023 - Elsevier
We report a flexible multi-modal mechanics language model, MeLM, applied to solve
various nonlinear forward and inverse problems, that can deal with a set of instructions …
various nonlinear forward and inverse problems, that can deal with a set of instructions …
Proteininvbench: Benchmarking protein inverse folding on diverse tasks, models, and metrics
Protein inverse folding has attracted increasing attention in recent years. However, we
observe that current methods are usually limited to the CATH dataset and the recovery …
observe that current methods are usually limited to the CATH dataset and the recovery …
Unleashing the power of artificial intelligence in materials design
The integration of artificial intelligence (AI) algorithms in materials design is revolutionizing
the field of materials engineering thanks to their power to predict material properties, design …
the field of materials engineering thanks to their power to predict material properties, design …
ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model
Through evolution, nature has presented a set of remarkable protein materials, including
elastins, silks, keratins and collagens with superior mechanical performances that play …
elastins, silks, keratins and collagens with superior mechanical performances that play …
BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio‐Inspired Materials
RK Luu, MJ Buehler - Advanced Science, 2024 - Wiley Online Library
The study of biological materials and bio‐inspired materials science is well established;
however, surprisingly little knowledge is systematically translated to engineering solutions …
however, surprisingly little knowledge is systematically translated to engineering solutions …
Navigating generative artificial intelligence promises and perils for knowledge and creative work
Generative artificial intelligence (GenAI) is rapidly becoming a viable tool to enhance
productivity and act as a catalyst for innovation across various sectors. Its ability to perform …
productivity and act as a catalyst for innovation across various sectors. Its ability to perform …
Untapped potential of deep eutectic solvents for the synthesis of bioinspired inorganic–organic materials
Since the discovery of deep eutectic solvents (DESs) in 2003, significant progress has been
made in the field, specifically advancing aspects of their preparation and physicochemical …
made in the field, specifically advancing aspects of their preparation and physicochemical …