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> 2024

Journal Papers​​​

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  • B.S. Grandey,  J. Dauwels,  Z.Y. Koh,  B. P. Horton,  L.Y. Chew, “Fusion of probabilistic projections of sea-level rise,” Earth's Future, 12, https://doi.org/10.1029/2024EF005295, Dec. 2024 (IF 7.3). PDF

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  • Z.Y. Koh, B.S. Grandey, D.Samanta, A.D.Switzer, B.P. Horton, J.Dauwels, and L.Y. Chew, “Tide–surge interaction observed at Singapore and the east coast of Peninsular Malaysia using a semi-empirical model,” Ocean Sci., 20, 1495–1511, https://doi.org/10.5194/os-20-1495-2024, 2024 (IF 4.1). PDF

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  • J.J. Halford, G.  Campobello, B.H. Brinkmann, M. Stead, S. Rampp, J. Rémi, K.B. Nilsen, J. Dauwels, M. Galanti, et al., Letter to the Editor: Announcement of a Call for Proposals for biomedical waveform coding. Clinical Neurophysiology, 165, 88-89, 2024. https://doi.org/10.1016/j.clinph.2024.06.010

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  • A. Piazzoni, J. Cherian, J. Dauwels and L. -P. Chau, "PEM: Perception Error Model for Virtual Testing of Autonomous Vehicles,"  IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 1, pp. 670-681, Jan. 2024 (IF 7.9). PDF

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  • L. Liu, X. Jiang, M. Saerbeck and J. Dauwels, "EAD-GAN: A Generative Adversarial Network for Disentangling Affine Transforms in Images," in IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 3, pp. 3652-3662, March 2024 (IF 10.2). PDF

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  • D. De Ridder, M.A. Siddiqi, J. Dauwels, W. A. Serdijn, C. Strydis, NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed?, Neuromodulation: Technology at the Neural Interface, Volume 27, Issue 4, 2024, Pages 711-729 (IF 2.8). PDF

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Conference Papers

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  • J. Yin, C. Meo, A. Roy, Z.B. Cher, M. Lică, Y. Wang, R. Imhoff, R. Uijlenhoet, and J. Dauwels, “Precipitation Nowcasting Using Physics Informed Discriminator Generative Models,” Proc. 24th European Signal Processing Conference (EUSIPCO 2024), 2024, Lyon, France.

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  • S. Li, D.B. Profeta, and J. Dauwels, “MoReSo: A DNN Framework Expediting Content-based Video Image Retrieval (CBVIR),” Proc. 24th European Signal Processing Conference (EUSIPCO 2024), 2024, Lyon, France. 

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  • A. Hamo, N. Ottenhof, J.W. Korstanje, and J. Dauwels, “Machine Learning Algorithm to Estimate Cardiac Output Based on Less-Invasive Arterial Blood Pressure Measurements,” Proc. 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2024), 2024, Orlando, FL.   

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  • S. Zhao, A. Hamo, N. Ottenhof, J.W. Korstanje, and J. Dauwels, “Prediction of Postinduction Hypotension by Machine Learning,” Proc. 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2024), 2024, Orlando, FL.   

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  • Z. Wang, R. Butler, and J. Dauwels, “Towards Robust Object Detection in Unseen Catheterization Laboratories,” IEEE Medical Measurements & Applications (MeMeA 2024), 2024, Eindhoven, Netherlands.  

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  • C. Meo, K. Sycheva, A. Goyal, and J. Dauwels, “Bayesian-LoRA: LoRA based Parameter Efficient Fine-Tuning using Optimal Quantization levels and Rank Values trough Differentiable Bayesian Gates,” Workshop on Advancing Neural Network Training at International Conference on Machine Learning (WANT@ICML 2024), 2024, Vienna, Austria.

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  • C. Meo, L. Mahon, A. Goyal and J. Dauwels, “alpha TC-VAE: On the relationship between Disentanglement and Diversity,” The Twelfth International Conference on Learning Representations (ICLR 2024), 2024, Vienna, Austria.

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  • C. Meo, A. Roy, M. Lica, Z. Boucher, J. Yin, Y. Wang, R. Imhoff, R. Uijlenhoet, and J. Dauwels, “Extreme Precipitation Nowcasting using Transformer-based generative models,” Workshop Tackling Climate Change with Machine Learning: Fostering the Maturity of ML Applications for Climate Change @ICLR 2024, 2024, Vienna, Austria.

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