[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations

A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".

This repository hosts a simple demonstration of a deep learning approach for the inverse design of patch antennas. The goal is to explore energy-efficient designs and to significantly reduce simulation cost compared to conventional methods.

Optimization and inverse design of photonic crystals using deep reinforcement learning

Silicon Photonics Design Tools.

A collection of inverse design challenges

PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design

Efficient GPU-computing simulation for differentiable crystal plasticity finite element method

Simple GUI for PROFOIL

IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics, KDD'23

Exposing Algorithmic Bias with Canonical Sets

Genetic Lookup for Apt Substances

BC-Design: A Biochemistry-Aware Framework for High-Precision Inverse Protein Folding

The code for the work presented in the research paper titled "***"

Algorithms for inverse design

Co-Optimization of Composition in CrabNet

Find optimal input of machine learning model.

Package for generating and inverse-designing 2D lattice materials. Represents lattices as heterogeneous graphs and utilizes message passing, automatic differentiation and surrogate gradients for the inverse design.

Custom types for topology optimization

OM-Diff: Inverse-design of organometallic catalysts with guided equivariant denoising diffusion