📝 All Publications

Alba Carballo-Castro, Sonia Laguna, Moritz Vandenhirtz, Julia E. Vogt (2024). Exploiting Interpretable Capabilities with Concept-Enhanced Diffusion and Prototype Networks. In NeurIPS 2024 (Oral) Workshop Interpretable AI.

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Karthik Gopinath, Andrew Hoopes, Daniel C. Alexander, Steven E. Arnold, Yael Balbastre, Benjamin Billot, Adrià Casamitjana, You Cheng, Russ Yue Zhi Chua, Brian L. Edlow, Bruce Fischl, Harshvardhan Gazula, Malte Hoffmann, C. Dirk Keene, Seunghoi Kim, W. Taylor Kimberly, Sonia Laguna, Kathleen E. Larson, Koen Van Leemput, Oula Puonti, Livia M. Rodrigues, Matthew S. Rosen, Henry F. J. Tregidgo, Divya Varadarajan, Sean I. Young, Adrian v. Dalca, Juan Eugenio Iglesias (2024). Synthetic data in generalizable, learning-based neuroimaging. In Imaging Neuroscience.

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Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphne Chopard, Julia E. Vogt (2024). Deep Generative Clustering With Multimodal Diffusion Variational Autoencoders. In ICLR 2024.

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Sonia Laguna, Julian Heidenreich, Jiugeng Sun, Nilüfer Cetin, Ibrahim Al Hazwani, Udo Schlegel, Furui Cheng, Mennatallah El-Assady (2023). ExpLIMEable: An exploratory framework for LIME. In NeurIPS 2023 Workshop XAI.

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Sonia Laguna, Riana Schleicher, Benjamin Billot, Pamela Schaefer, Brenna McKaig, Joshua N. Goldstein, Kevin N. Sheth, Matthew S. Rosen, W. Taylor Kimberly, Juan Eugenio Iglesias (2022). Super-resolution of portable low-field MRI in real scenarios: integration with denoising and domain adaptation. In MIDL (Medical Imaging with Deep Learning Conference) 2022.

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Clara Gomez-Cruz*, Sonia Laguna*, Ariadna Bachiller-Pulido, Cristina Quilez, Marina Cañadas-Ortega, Ignacio Albert-Smet, Jorge Ripoll, Arrate Muñoz-Barrutia (2022). Single Plane Illumination Microscopy for Microfluidic Device Imaging. In Biosensors.

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Juan Eugenio Iglesias, Riana Schleicher, Sonia Laguna, Benjamin Billot, Pamela Schaefer, Brenna McKaig, Joshua N. Goldstein, Kevin N. Sheth, Matthew S. Rosen, W. Taylor Kimberly (2022). Quantitative Brain Morphometry of Portable Low-Field-Strength MRI Using Super-Resolution Machine Learning. In Radiology.

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