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Conditional Flow Matching for Bayesian Posterior Inference
So Won Jeong, Percy S. Zhai, Veronika Ro\v{c}ov\'a
https://arxiv.org/abs/2510.09534 https://…

Conditional Flow Matching for Bayesian Posterior Inference
We propose a generative multivariate posterior sampler via flow matching. It offers a simple training objective, and does not require access to likelihood evaluation. The method learns a dynamic, block-triangular velocity field in the joint space of data and parameters, which results in a deterministic transport map from a source distribution to the desired posterior. The inverse map, named vector rank, is accessible by reversibly integrating the velocity over time. It is advantageous to levera…

Insights into the OER, ORR, and HER Activity of a New MXene-Family SnSiGeN4 Photocatalyst for Water Splitting: A First-Principles Study
Chhatra Bahadur Subba, Bhanu Chettri, Amel Laref, Zeesham Abbas, Amna Parveen, Dibya Prakash Rai, Zaithanzauva Pachuau
https://arxiv.org/abs/2510.09538

Insights into the OER, ORR, and HER Activity of a New MXene-Family SnSiGeN4 Photocatalyst for Water Splitting: A First-Principles Study
The development of efficient and cost-effective catalysts for clean energy conversion remains a central challenge in materials science. Although platinum serves as the benchmark catalyst, its scarcity and high cost hinder large-scale deployment. In this study, we propose a newly predicted SnSiGeN4 MXene-family monolayer as a promising candidate for the oxygen evolution reaction (OER), oxygen reduction reaction (ORR), and hydrogen evolution reaction (HER). Using first-principles calculations, we…