The Intelligence for Design, Engineering, And Learning (IDEAL) Lab's repositories
airfoil-opt-gan
Experiment code associated with our paper: "Aerodynamic Design Optimization and Shape Exploration using Generative Adversarial Networks"
bezier-gan
BĂ©zier Generative Adversarial Networks
IH-GAN_CMAME_2022
IH-GAN, data generation, and topology optimization code associated with our accepted CMAME 2022 paper: "IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures."
design-data-list
A list of open-source or otherwise available datasets for various applications and papers within Mechanical Engineering as well as Design more broadly.
CEBGAN_JMD_2021
CEBGAN and airfoil optimization code associated with our accepted JMD 2021 paper: "Inverse Design of 2D Airfoils using Conditional Generative Models and Surrogate Log-Likelihoods."
design_embeddings_jmd_2016
Experiment code associated with our JMD paper: "Design Manifolds Capture the Intrinsic Complexity and Dimension of Design Spaces"
OptimizingDiffusionSciTech2024
Dataset for the paper presented at SciTech 2024 "Optimizing Diffusion to Diffuse Optimal Designs"
ideallab.github.io
IDEAL Lab website repository
Active-Expansion-Sampling
Experiment code associated with our paper: "Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space"
domain_expansion_jmd_2017
Experiment code associated with our JMD paper: "Beyond the Known: Detecting Novel Feasible Domains over an Unbounded Design Space"
hgan_jmd_2019
Experiment code associated with our JMD 2019 paper: "Synthesizing Designs with Inter-part Dependencies Using Hierarchical Generative Adversarial Networks"
ID_Conduction_IDETC2022
Machine learning models and 2D heat sink topology optimization code associated with our accepted IDETC 2022 paper: "Mean Squared Error may lead you astray when Optimizing your Inverse Design methods."
hgan_idetc2018
Experiment code associated with our IDETC 2018 paper: "Synthesizing Designs with Inter-part Dependencies Using Hierarchical Generative Adversarial Networks"
JMD-Diversity-in-Bayesian-Optimization
Code to support the experiments published in "How Diverse Initial Samples Help and Hurt Bayesian Optimizers" in the Journal of Mechanical Design
Optimal_Airfoil_Geometry_IDETC2022
Machine learning models and 2D airfoil dimensionality reduction code associated with our accepted IDETC 2022 paper: "Effect of Optimal Geometries and Performance Parameters on Airfoil Latent Space Dimension."
design-variety
Experiment code and data associated with our IDETC paper titled "Measuring and Optimizing Design Variety using Herfindahl Index"
onlinematching
Experiment code associated with our JMD paper: "Forming Diverse Teams from Sequentially Arriving People"
d3-deadlines
:alarm_clock: AI conference deadline countdowns
dcc-deep-learning-workshop
GitHub site for DCC '18 Workshop on Learning Design Representations: Deep Learning and Beyond
GRAN
Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019
Learn_to_compose_IDETC_2020
DeCNN, GNN, and pipe flow simulation code associated with our accepted IDETC 2020 paper: "Learning to Abstract and Compose Mechanical Device Function and Behavior."