LAMM: MIT Laboratory for Atomistic and Molecular Mechanics

PDF2Audio. Jupyter Notebook

SciAgentsDiscovery. Python

GraphReasoning. Jupyter Notebook

PRefLexOR. Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning

AtomAgents. Forth

HyperGraphReasoning. HTML

MeLM. Jupyter Notebook

Graph-Aware-Transformers. Graph-Aware Attention for Adaptive Dynamics in Transformers

LifeGPT. Jupyter Notebook

ModeShapeDiffusionDesign. Jupyter Notebook

ProtAgents. Jupyter Notebook

MechAgents. Agent-based LLM modeling of mechanics problems

ProteinDiffusionGenerator. Generative method to design novel proteins using a diffusion model

FieldPredictorGAN. Deep learning model to predict complex stress and strain fields in hierarchical composites

LLM-finetuning. Python

HierarchicalDesign. A computational building block approach towards multiscale architected materials analysis and design with application to hierarchical metal metamaterials

ProteinMechanicsDiffusionDesign. Jupyter Notebook

Sparks. Multi-modal, multi-agent AI system capable of independently conducting research by formulating hypotheses, performing experiments, and adapting its strategy

MoleculeDiffusionTransformer. Molecular generation using diffusion models and autoregressive transformer models

FieldCompleter. GAN/convolutional and Transformer models to predict missing mechanical information given limited known data in part of the domain, and further characterize the composite geometries from the recovered mechanical fields for 2D and 3D complex microstructures

Cephalo-Phi-3-Vision-MoE. Python

MateriomicTransformer. Generative Pretrained Autoregressive Transformer Graph Neural Network applied to the Analysis and Discovery of Materials

atomic2field. Codes for translating structural defects to atomic properties

DynaGen. The DynaGen model allows the prediction of dynamical field data based on microstructure input. The model is exemplified to dynamic fracture problems in brittle materials.

Cephalo. Jupyter Notebook

PeptideMiner. Jupyter Notebook

ProteinSwarm. Python

LeafGAN. Jupyter Notebook

SilkomeGPT. Generative strategies for modeling, design and analysis of silk protein sequences for enhanced mechanical properties

GraphGeneration. GraphGeneration: Modeling and design of hierarchical bio-inspired de novo spider web structures using deep learning and additive manufacturing

DyFraNet. Jupyter Notebook

CollagenTransformer. CollagenTransformer: End-to-End Transformer Model to Predict Thermal Stability of Collagen Triple Helices Using an NLP Approach

BEAVER. Python

LLMsxPlants. Jupyter Notebook

SparksMatter. Python

graph-preflexor-grpo. Jupyter Notebook

MusicAnalysis. Music analysis tools especially around scales, defects and related topics

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

MolShapeGAN. Jupyter Notebook

SilkomeMD. Shell

marker. Convert PDF to markdown quickly with high accuracy

Falcon-Programming-Language. The Falcon Programming Language.

ProteinMechanicsGNN. Rapid Prediction of Protein Natural Frequencies using Graph Neural Networks

SpiderPDB. PDB files of spider silk structures

Cephalo-Idefics2-MoE. Python

MNNN. Python

InstantMesh. InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

FieldPerceiver. Field-to-field translation

GenerativeDiffusionImages. Jupyter Notebook

mergekit-Phi3-V. Tools for merging pretrained large language models.

fast-perceiver. Fast and memory efficient PyTorch implementation of the Perceiver with FlashAttention.

InterPLM. Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders

GNN-collective-cell-dynamics. Python

imagen-pytorch. Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch

HardnessMapDesign. Jupyter Notebook