Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 218,356
Number of items: 218,356
  • Open Access
    Pucci, N., Ujčič-Voortman, J., Verhoeff, A. P., & Mende, D. R. (2025). Priority effects, nutrition and milk glycan-metabolic potential drive Bifidobacterium longum subspecies dynamics in the infant gut microbiome. PeerJ, 13, Article e18602. https://doi.org/10.7717/peerj.18602
  • Open Access
    Mölleby, F. U., Ojiako-Chijioke, C., Hoàng, N. N. P., Chan, Y.-H. A., & Nack, F. (2025). A Critical View on the Need for Adaptation and AI Services in IDN Authoring. In M. C. Reyes, & F. Nack (Eds.), Interactive Storytelling : 18th International Conference on Interactive Digital Storytelling, ICIDS 2025, Saint Julian, Malta, December 1–5, 2025 : proceedings (Vol. I, pp. 32-53). (Lecture Notes in Computer Science; Vol. 16374 ). Springer. https://doi.org/10.1007/978-3-032-12408-1_3
  • Open Access
    Verveen, A., Verfaillie, S. C. J., Visser, D., Koch, D. W., Verwijk, E., Geurtsen, G. J., Roor, J., Appelman, B., Boellaard, R., van Heugten, C. M., Horn, J., Hulst, H. E., de Jong, M. D., Kuut, T. A., van der Maaden, T., van Os, Y. M. G., Prins, M., Visser-Meily, J. M. A., van Vugt, M., ... Knoop, H. (2025). Neuropsychological functioning after COVID-19: Minor differences between individuals with and without persistent complaints after SARS-CoV-2 infection. The Clinical Neuropsychologist, 39(2), 347-362. https://doi.org/10.1080/13854046.2024.2379508
  • Open Access
    Gerdes, M., de Haan, P., Bondesan, R., & Cheng, M. C. N. (2025). Nonperturbative trivializing flows for lattice gauge theories. Physical Review D, 112(9), Article 094516. https://doi.org/10.1103/31d5-hvp6
  • Open Access
    Tello, A., & Degeler, V. (2025). Contrasting Global and Local Representations for Human Activity Recognition using Graph Neural Networks. In The 40th Annual ACM Symposium on Applied Computing : March 31-April 4, 2025 (pp. 630-637). Association for Computing Machinery. https://doi.org/10.1145/3672608.3707743
  • Open Access
    Chatterji, S., & Acar, E. (2025). Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning. In I. Lynce, N. Murano, M. Vallati, S. Villata, F. Chesani, M. Milano, A. Omicini, & M. Dastani (Eds.), ECAI 2025: 28th European Conference on Artificial Intelligence, 25-30 October2025, Bologna, Italy : including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025) : proceedings (pp. 2538-2545). (Frontiers in Artificial Intelligence and Applications; Vol. 413). IOS Press. https://doi.org/10.48550/arXiv.2411.04867, https://doi.org/10.3233/FAIA251103
  • Open Access
    Bindila, L., Eid, T., Mills, J. D., Hildebrand, M. S., Brennan, G. P., Masino, S. A., Whittemore, V., Perucca, P., Reid, C. A., Patel, M., Wang, K. K., & van Vliet, E. A. (2025). A companion to the preclinical common data elements for proteomics, lipidomics, and metabolomics data in rodent epilepsy models: A report of the TASK3-WG4 omics working group of the ILAE/AES joint translational TASK force. Epilepsia Open, 10(S1), S206-S237. https://doi.org/10.1002/epi4.12662
  • Open Access
    Mousavian, M., Abbasiantaeb, Z., Aliannejadi, M., & Crestani, F. (2025). Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement. In ICTIR '25: Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval (ICTIR) : July 18, 2025, Padua, Italy (pp. 56-66). Association for Computing Machinery. https://doi.org/10.1145/3731120.3744620
  • Open Access
    Majumder, A., Simionescu, A., Plšek, T., Brienza, M., Churazov, E., Khabibullin, I., Gastaldello, F., Botteon, A., Röttgering, H., Brüggen, M., Lyskova, N., Rajpurohit, K., Sunyaev, R. A., & Wise, M. W. (2025). X-ray investigation of the remarkable galaxy group Nest200047. Astronomy and Astrophysics, 699, Article A375. https://doi.org/10.1051/0004-6361/202554682
  • Open Access
    Skyllas, N., Verhoeven, M. A., Loonen, M. J. J. E., & Bintanja, R. (2025). Simulating and Analysing Seabird Flyways: An Approach Combining Least-Cost Path Modelling and Machine Learning. Global Ecology and Biogeography, 34(2), Article e70016. https://doi.org/10.1111/geb.70016
Page 353 of 21836