Sonia Laguna
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    • RadVLM: A Multitask Conversational Vision-Language Model for Radiology
    • Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable
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    • Automatic Classification of General Movements in Newborns
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    • Deep Generative Clustering With Multimodal Diffusion Variational Autoencoders
    • ExpLIMEable: An exploratory framework for LIME
    • Super-resolution of portable low-field MRI in real scenarios: integration with denoising and domain adaptation
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    • 🏛️ Started a research stay at University of Cambridge!
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    • 🗣️ Our Workshop on GenAI meets XAI was accepted!
    • 📝 Our two main conference papers on Concept Bottleneck Models got accepted at Neurips 2024!
    • 📝 Our two workshop papers got accepted at Neurips 2024!
    • 🖥️ Joined Google as a Research Intern and later extended as a Student Researcher.
    • 📝 Our main conference paper on Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders got accepted at ICLR 2024!
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    • 🗣️ Our Workshop on Deep Generative Models for Health was accepted!
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    • 🏛️ Started the MSc in D-ITET at ETH Zurich!
    • 🏛️ Selected as Amgen Scholar to do research at ETH Zurich!
    • 🏛️ Started an exchange year at Georgia Institute of Technology!
    • 🏛️ Started my BSc in Biomedical Engineering at Universidad Carloss III de Madrid!
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Deep Generative Clustering With Multimodal Diffusion Variational Autoencoders

Apr 24, 2024·
Emanuele Palumbo
,
Laura Manduchi
Sonia Laguna
Sonia Laguna
,
Daphne Chopard
,
Julia E. Vogt
· 0 min read
PDF Code
Type
Conference paper
Publication
In ICLR 2024
Last updated on Apr 24, 2024
Sonia Laguna
Authors
Sonia Laguna
PhD in Machine Learning @ETH Zurich
← Synthetic data in generalizable, learning-based neuroimaging Oct 15, 2024
ExpLIMEable: An exploratory framework for LIME Dec 24, 2023 →

© 2025 Sonia Laguna. This work is licensed under CC BY NC ND 4.0

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