A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".
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Updated
Mar 24, 2023 - Python
A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".
[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations
Optimization and inverse design of photonic crystals using deep reinforcement learning
gRNAde: Geometric Deep Learning for 3D RNA inverse design
Silicon Photonics Design Tools.
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.
PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design
[ICLR24] CinDM uses compositional generative models to design boundaries and initial states significantly more complex than the ones seen in training for physical simulation
Inverse Design of PIC devices for generating coherent optical lattice in a 2D slab region.
Find optimal input of machine learning model.
Genetic Lookup for Apt Substances
Mapping properties to molecules in QM7-X
Co-Optimization of Composition in CrabNet
Simulation and Optimization Library for Integrated Optics in Julia.
Data and Codes for Experimentally Validated Inverse design of Multi-Property Fe-Co-Ni alloys
The code for the work presented in the research paper titled "***"
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.
IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics, KDD'23
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