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de Reus, P., Dresen, K., Oprescu, A., Irion, K., & Kolk, A. (2024). An interdisciplinary exploration of trade-offs between energy, privacy and accuracy aspects of data. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2410.00069 -
Wu, D., Lei, Y., Yates, A., & Monz, C. (2024). Representational Isomorphism and Alignment of Multilingual Large Language Models. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), The 2024 Conference on Empirical Methods in Natural Language Processing : Findings of EMNLP 2024: EMNLP 2024 : November 12-16, 2024 (pp. 14074-14085). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-emnlp.823 -
Deng, K.-Z., Sukowski, V., & Fernández-Ibáñez, M. Á. (2024). Non-Directed C−H Arylation of Anisole Derivatives via Pd/S,O-Ligand Catalysis. Angewandte Chemie, 136(19), Article e202400689. https://doi.org/10.1002/ange.202400689, https://doi.org/10.1002/anie.202400689 -
Thanh Si, N., Vu Nhat, P., Vo Anh Duy, N., Thi Bao Trang, N., Nhan Tran, T., Chi Ben, N., Anh Nguyen, T., Triet Dang, M., Schall, P., & An Dinh, V. (2024). Polaronic defect enhances optoelectronic and transport properties of blue phosphorene quantum dots using first-principles methods. Computational materials science, 241, Article 113020. https://doi.org/10.1016/j.commatsci.2024.113020 -
Föllmer, B., Williams, M. C., Dey, D., Arbab-Zadeh, A., Maurovich-Horvat, P., Volleberg, R. H. J. A., Rueckert, D., Schnabel, J. A., Newby, D. E., Dweck, M. R., Guagliumi, G., Falk, V., Vázquez-Mézquita, A. J., Biavati, F., Išgum, I., & Dewey, M. (2024). Roadmap on the Use of Artificial Intelligence for Imaging of Vulnerable Atherosclerotic Plaque in Coronary Arteries. Nature Reviews. Cardiology, 21(1), 51-64. https://doi.org/10.1038/s41569-023-00900-3 -
Mohamed, R., Avgeris, M., Leivadeas, A., & Lambadaris, I. (2024). Optimizing Resource Fragmentation in Virtual Network Function Placement Using Deep Reinforcement Learning. IEEE Transactions on Machine Learning in Communications and Networking, 2, 1475-1491. https://doi.org/10.1109/TMLCN.2024.3469131 -
Evers, K., Farisco, M., & Pennartz, C. M. A. (2024). Assessing the commensurability of theories of consciousness: On the usefulness of common denominators in differentiating, integrating and testing hypotheses. Consciousness and Cognition, 119, Article 103668. https://doi.org/10.1016/j.concog.2024.103668 -
Kuric, D., Infante, G., Gómez, V., Jonsson, A., & van Hoof, H. (2024). Planning with a Learned Policy Basis to Optimally Solve Complex Tasks. In S. Bernardini, & C. Muise (Eds.), Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling: June 1–6, 2024, Alberta, Canada (pp. 333-341). (ICAPS; Vol. 34). AAAI Press. https://doi.org/10.1609/icaps.v34i1.31492 -
Yiasemis, G., Sánchez, C. I., Sonke, J.-J., & Teuwen, J. (2024). On retrospective k-space subsampling schemes for deep MRI reconstruction. Magnetic resonance imaging, 107, 33–46. https://doi.org/10.1016/j.mri.2023.12.012
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