Assessing the adoption of the FAIR principles in Italian environmental research infrastructures [0.03%]
评估FAIR原则在意大利环境研究基础设施中采用情况的影响因素
Enrica Nestola,Gregorio Sgrigna,Gianmarco Ingrosso et al.
Enrica Nestola et al.
This study investigates the adoption of the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by 14 environmental research infrastructures (RIs) operating at the Italian level. Through a three-step process (surveys, interv...
Thomas Burger
Thomas Burger
Generative artificial intelligence can be used to create realistic new data, even for complex real-world processes that cannot be exhaustively modeled: the model is simply learned from preexisting data. Generative artificial intelligence is...
Mainzelliste: Ten years of pseudonymization, record linkage, and informed consent management [0.03%]
主记录表： псudos匿名化、记录连接和知情同意管理的十年
Galina Tremper,Torben Brenner,Moanes Ben Amor et al.
Galina Tremper et al.
Record linkage and pseudonymization are crucial tasks in collaborative biomedical research. Data for a patient are rarely stored in one place and therefore often need to be linked and integrated across multiple institutions. Mainzelliste is...
The inadequacy of offline large language model evaluations: A need to account for personalization in model behavior [0.03%]
离线大型语言模型评估的不足：需要考虑模型行为中的个性化因素
Angelina Wang,Daniel E Ho,Sanmi Koyejo
Angelina Wang
Standard offline evaluations for language models fail to capture how these models actually behave in practice, where personalization fundamentally alters model behavior. In this work, we provide empirical evidence showcasing this phenomenon...
Unraveling learning characteristics of transformer models for molecular design [0.03%]
探究变换器模型在分子设计中的学习特性
Jannik P Roth,Jürgen Bajorath
Jannik P Roth
In drug design, transformer networks adopted from natural language processing are applied in a variety of ways. We have used sequence-based generative compound design as a model system to explore the learning characteristics of transformers...
Three-factor learning in spiking neural networks: An overview of methods and trends from a machine learning perspective [0.03%]
脉冲神经网络中的三因素学习：从机器学习角度的方法和趋势综述
Szymon Mazurek,Jakub Caputa,Jan K Argasiński et al.
Szymon Mazurek et al.
Three-factor learning rules in spiking neural networks (SNNs) have emerged as a crucial extension of traditional Hebbian learning and spike-timing-dependent plasticity (STDP), incorporating neuromodulatory signals to improve adaptation and ...
David Fernandez Bonet,Johanna I Blumenthal,Shuai Lang et al.
David Fernandez Bonet et al.
DNA barcode networks are the basis of sequencing-based microscopy, an emerging family of chemical imaging methods aiming to reconstruct spatial information, without optics, using sequencing technology. These methods capture microscopic spat...
AISleep: Automated and interpretable sleep staging from single-channel EEG data [0.03%]
基于单通道EEG数据的自动且可解释的睡眠分期:AISleep算法
Xun Mai,Binghua Song,Manli Luo et al.
Xun Mai et al.
Sleep staging is essential for understanding sleep physiology and diagnosing sleep-related disorders. However, traditional manual scoring is time-consuming and resource intensive, limiting its scalability for large-scale application. In thi...
Julie R Pivin-Bachler,Egon L van den Broek
Julie R Pivin-Bachler
Ranging from health to cybersecurity, real-world data are heavily imbalanced. Handling imbalance is among the formidable challenges of machine learning (ML), as it deteriorates ML's performance, yielding biased results toward majority class...
Neural mechanisms of visual quality perception and adaptability in the visual pathway [0.03%]
视觉通路中视觉质量感知和适应性的神经机制
Yiming Zhang,Yitong Chen,Ying Hu et al.
Yiming Zhang et al.
Visual quality assessment (VQA) is indispensable in multimedia for evaluating algorithm effectiveness and optimizing systems, yet its neurobiological mechanisms remain poorly understood. Using functional magnetic resonance imaging (fMRI), w...