arXiv Machine Learning July 15, 2026 By Sarina Kopf, Cristina Nevado, Philippe Schwaller

Sample Efficient Generative Optimization for Molecular Design

Read the original on arXiv Machine Learning →

arXiv:2607. 12488v1 Announce Type: new Abstract: Molecular optimization in drug discovery, materials design, and catalysis requires searching vast chemical spaces under tight evaluation budgets, since high-fidelity oracles and experimental measurements are costly.

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

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