@inproceedings{
jung2024conditional,
title={Conditional Synthesis of 3D Molecules with Time Correction Sampler},
author={Hojung Jung and Youngrok Park and Laura Schmid and Jaehyeong Jo and Dongkyu Lee and Bongsang Kim and Se-Young Yun and Jinwoo Shin},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=gipFTlvfF1}
}
Diffusion models have demonstrated remarkable success in various domains, including molecular generation. However, conditional molecular generation remains a fundamental challenge due to an intrinsic trade-off between targeting specific chemical properties and generating meaningful samples from the data distribution. In this work, we present Time-Aware Conditional Synthesis (TACS), a novel approach to conditional generation on diffusion models. It integrates adaptively controlled plug-and-play "online" guidance into a diffusion model, driving samples toward the desired properties while maintaining validity and stability. A key component of our algorithm is our new type of diffusion sampler, Time Correction Sampler (TCS), which is used to control guidance and ensure that the generated molecules remain on the correct manifold at each reverse step of the diffusion process at the same time. Our proposed method demonstrates significant performance in conditional 3D molecular generation and offers a promising approach towards inverse molecular design, potentially facilitating advancements in drug discovery, materials science, and other related fields.
Conditional Synthesis of 3D Molecules with Time Correction Sampler
Hojung Jung Youngrok Park Laura Schmid Jaehyeong Jo Dongkyu Lee Bongsang Kim Se-Young Yun Jinwoo Shin