arXiv Machine Learning August 18, 2026 By Kiran K. Yalamanchi, Pinaki Pal, Balaji Mohan, Abdullah S. AlRamadan, Jihad A. Badra, Yuanjiang Pei

A Generative Deep Learning Workflow for Inverse Molecular Design of Fuels

Read the original on arXiv Machine Learning →

arXiv:2504. 12075v4 Announce Type: replace Abstract: In the present work, a generative deep learning framework combining a Co-optimized Variational Autoencoder (Co-VAE) with quantitative structure-property relationship (QSPR) techniques is developed to enable inverse molecular design of fuels.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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