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New BOBa framework optimizes candidate selection in massive chemical spaces

By PulseAugur Editorial · [2 sources] ·

Researchers have developed BOBa, a new bandit-guided surrogate optimization framework designed to tackle the computational challenges of identifying high-utility candidates from massive discrete spaces, such as in drug discovery. This framework eliminates the need for full-library surrogate inference by adaptively allocating computation across different partitions of the action space. By treating these partitions as arms in a multi-armed bandit, BOBa focuses inference and evaluations on the most promising partitions while ensuring principled exploration, offering a tunable tradeoff between screening performance and computational cost. AI

IMPACT This framework could accelerate scientific discovery by improving the efficiency of searching through vast chemical or molecular libraries.

RANK_REASON The cluster contains a research paper detailing a new computational framework for optimization problems.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New BOBa framework optimizes candidate selection in massive chemical spaces

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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Mohammad Haddadnia, Yuvan Chali, Abhilash Jayaraj, Constance Kraay, Joana Reis, Felix Strieth-Kalthoff, Haribabu Arthanari ·

    Target-Aware Bandit Allocation for Scalable Surrogate Optimization in Chemical Space

    arXiv:2606.26657v1 Announce Type: new Abstract: Identifying high-utility candidates from massive discrete spaces under expensive evaluations is a recurring challenge across the sciences, with structure-based drug discovery as a prominent example. While surrogate-based optimizatio…

  2. arXiv cs.LG TIER_1 English(EN) · Haribabu Arthanari ·

    Target-Aware Bandit Allocation for Scalable Surrogate Optimization in Chemical Space

    Identifying high-utility candidates from massive discrete spaces under expensive evaluations is a recurring challenge across the sciences, with structure-based drug discovery as a prominent example. While surrogate-based optimization can increase sample efficiency by reducing the…

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