The integration of multi-scale neural dynamics remains a fundamental challenge in computational neuroscience. This paper introduces a novel mathematical framework that integrates stochastic differential equations with graph neural networks to model multi-scale brain dynamics. Our approach treats neural activity, synapt...
Md Taufiq Nasseef· International Journal of Ana...· 0 citations
Data, trained models and code behind STEPHY: A Graph Neural Inference Framework for Rapid Estimation of Regional Epidemic Dynamics from Large Viral Phylogenies (https://doi.org/10.21203/rs.3.rs-10631496/v2). This deposit holds what the paper's results are made of: the simulation benchmark, the trained models, the Danis...
Leke Lyu· Zenodo (CERN European Organi...· 0 citations
Colorectal cancer (CRC) is one of the most lethal malignancies worldwide, and the precise identification of biomarkers from colonic adenoma to cancer is of great significance for preventing the development of adenocarcinoma. Given that existing methods inadequately capture the topological network relationships among ge...
Yue Yuan, Yu Liu, Jingchun Fan et al.· PLoS ONE· 0 citations
Background Graph attention networks (GATs) are increasingly applied to transcriptomic data because they integrate gene-network structure while producing attention weights that are often interpreted as indicators of biological importance. However, whether attention-derived explanations reliably reflect biologically mean...
Nehal M. Ali· PLoS ONE· 0 citations
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Cancer subtype classification based on molecular features is important for characterizing tumor heterogeneity, evaluating patient prognosis, and supporting precision treatment. Multi-omics integration provides complementary molecular information across genomic, epigenomic, transcriptomic, and proteomic levels. Howeve...
Ke Wang, Jin-Bo Zheng, Lu-Lu Zhao et al.· BMC Bioinformatics· 0 citations
Graph Neural Networks (GNNs) have demonstrated remarkable performance on graph-based learning tasks and are increasingly deployed in security-critical applications. However, recent studies have shown that they are highly vulnerable to graph backdoor attacks (GBAs), where adversaries implant malicious triggers to induce...
Abstract Artificial Intelligence in general and Machine Learning (ML) in particular has the potential to play a key role in critical infrastructure such as Water Distribution Systems (WDSs). In the face of urban population growth, ML can pave the way towards smart cities by not only solving various tasks in WDSs but al...
Inaam Ashraf, André Artelt, David P. Leins et al.· Lecture notes in computer sc...· 0 citations
For four decades the central oncogenic drivers of human cancer the RAS GTPases, the transcription-factor MYC, mutant p53, and the protein-tyrosine phosphatases, fusion oncoproteins and intrinsically disordered regulators that surround them were regarded as undruggable: lacking deep, well-defined small-molecule binding...
Mikołaj Stańczak, Sarfaraz K. Niazi· Pharmaceuticals· 0 citations
This dataset provides synchronized, high-resolution multi-physics measurements collected by IMOS-EPFL in collaboration with Aalborg University using the controlled district heating testbed at the Smart Water Infrastructures Laboratory (SWIL), Aalborg University, Denmark. The data were collected as part of the Intellige...
Keivan Faghih Niresi, Christian Møller Jensen, Carsten Skovmose Kallesøe et al.· Zenodo (CERN European Organi...· 0 citations
Photodynamic therapy (PDT) is a minimally invasive therapeutic approach based on the light-induced activation of a photosensitizer in the presence of molecular oxygen, resulting in the generation of reactive oxygen species, including singlet oxygen. Despite local selectivity and low systemic toxicity, reproducibility o...
R. Marunych, D. Bartusik-Aebisher, Klaudia Dynarowicz et al.· International Journal of Mol...· 0 citations
The precise delineation of urban land use, particularly mixed land use, is essential for sustainable urban planning and resource allocation. However, traditional pixel-based mapping methods face a profound "semantic gap" and struggle to decode the complex, overlapping functional dynamics of modern cities. This study pr...
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
MIT News · Artificial Intelligence· news.mit.eduJul 15, 2026
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
