Ordered embeddings and intrinsic dimensionalities with information-ordered bottlenecks by Matthew Ho, Xiaosheng Zhao, Benjamin D Wandelt

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WEISS: Wasserstein efficient sampling strategy for LLMs in drug design by Riccardo Tedoldi, Junyong Li, Ola Engkvist, Andrea Passerini, Annie M Westerlund, Alessandro Tibo

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Satellite image classification with neural quantum kernels by Pablo Rodriguez-Grasa, Robert Farzan-Rodriguez, Gabriele Novelli, Yue Ban, Mikel Sanz

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FFTL-Net: a network for the classification of skin diseases based on feature fusion and transfer learning by Xiaowei Song, Yurong Mei, Zhilei Zhao, Hao Chang, Lina Han, Hui Wang, Xinyi Zhang, Guoqiang Wang

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Variational autoencoders for at-source data reduction and anomaly detection in high energy particle detectors by Alexander Yue, Haoyi Jia, Julia Gonski

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Adaptive continuous-discrete variables optimization for active learning with extremely sparse data in optical material design by Serang Jung, Eungkyu Lee

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Stabilizing training of affine coupling layers for high-dimensional variational inference by Daniel Andrade

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Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics by Kenji Ueda, Masaki Nishiura

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Coupled CANN-DEM simulation in solid mechanics by Stefan Hildebrand, Jonathan Georg Friedrich, Melika Mohammadkhah, Sandra Klinge

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Predicting the von Neumann entanglement entropy using a graph neural network by Anas Saleh

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LatentDE: latent-based directed evolution for protein sequence design by Thanh V T Tran, Nhat Khang Ngo, Viet Thanh Duy Nguyen, Truong-Son Hy

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Improving thermal state preparation of Sachdev–Ye–Kitaev model with reinforcement learning on quantum hardware by Akash Kundu

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VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities by Shray Mathur, Noah van der Vleuten, Kevin G Yager, Esther H R Tsai

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First-passage approach to optimizing perturbations for improved training of machine learning models by Sagi Meir, Tommer D Keidar, Shlomi Reuveni, Barak Hirshberg

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Considering the ethics of large machine learning models in the chemical sciences by Evan Walter Clark Spotte-Smith

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Into the latent space of capacitive sensors: interpolation and synthetic data generation using variational autoencoders by Miguel Monteagudo Honrubia, Francisco Javier Herraiz-Martínez, Javier Matanza Domingo

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A genetic algorithm to generate maximally orthogonal frames in complex space by Sebastián Roca-Jerat, Juan Román-Roche

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Chemical space-informed machine learning models for rapid predictions of x-ray photoelectron spectra of organic molecules by Susmita Tripathy, Surajit Das, Shweta Jindal, Raghunathan Ramakrishnan

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Multi-fidelity transfer learning for quantum chemical data using a robust density functional tight binding baseline by Mengnan Cui, Karsten Reuter, Johannes T Margraf

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Bridging text and crystal structures: literature-driven contrastive learning for materials science by Yuta Suzuki, Tatsunori Taniai, Ryo Igarashi, Kotaro Saito, Naoya Chiba, Yoshitaka Ushiku, Kanta Ono

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