The Informatics for Design, Engineering, And Learning (IDEAL) Lab (IDEALLab)

The Informatics for Design, Engineering, And Learning (IDEAL) Lab

IDEALLab

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GitHub repositories for the Informatics for Design, Engineering, And Learning (IDEAL) Lab

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The Informatics 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"

Language:PythonLicense:MITStargazers:56Issues:9Issues:1

bezier-gan

BĂ©zier Generative Adversarial Networks

Language:PythonLicense:MITStargazers:37Issues:5Issues:12

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."

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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."

Language:Jupyter NotebookLicense:MITStargazers:7Issues:3Issues:0

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.

design_embeddings_jmd_2016

Experiment code associated with our JMD paper: "Design Manifolds Capture the Intrinsic Complexity and Dimension of Design Spaces"

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ideallab.github.io

IDEAL Lab website repository

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Active-Expansion-Sampling

Experiment code associated with our paper: "Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space"

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midbench

The Maryland Inverse Design Benchmark Suite

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OptimizingDiffusionSciTech2024

Dataset for the paper presented at SciTech 2024 "Optimizing Diffusion to Diffuse Optimal Designs"

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domain_expansion_jmd_2017

Experiment code associated with our JMD paper: "Beyond the Known: Detecting Novel Feasible Domains over an Unbounded Design Space"

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hgan_jmd_2019

Experiment code associated with our JMD 2019 paper: "Synthesizing Designs with Inter-part Dependencies Using Hierarchical Generative Adversarial Networks"

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ranking_diversity_jmd_2017

Experiment code associated with JMD paper: "Ranking ideas for diversity and quality"

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hgan_idetc2018

Experiment code associated with our IDETC 2018 paper: "Synthesizing Designs with Inter-part Dependencies Using Hierarchical Generative Adversarial Networks"

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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."

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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

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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."

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design-variety

Experiment code and data associated with our IDETC paper titled "Measuring and Optimizing Design Variety using Herfindahl Index"

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idea_map

Experiment code associated with our JMD paper: "Unpacking subjective creativity ratings: Using triplet queries to find idea maps"

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onlinematching

Experiment code associated with our JMD paper: "Forming Diverse Teams from Sequentially Arriving People"

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bisonet

Dataset for paper titled ''Creative Exploration Using Topic Based Bisociative Networks''

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d3-deadlines

:alarm_clock: AI conference deadline countdowns

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dcc-deep-learning-workshop

GitHub site for DCC '18 Workshop on Learning Design Representations: Deep Learning and Beyond

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FinDeR

Website repository for the Frontiers in Design Representation Summer School

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G2SAT

G2SAT: Learning to Generate SAT Formulas

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GRAN

Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019

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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."

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