A Robotic Surgery Platform for Automated Tissue Micromanipulation in Zebrafish Embryos

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A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (5/6)

Jean-Philippe Thiran, Roser Vinals Terres

This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

EPFL Infoscience2024

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (6/6)

Jean-Philippe Thiran, Roser Vinals Terres

EPFL Infoscience2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Understanding generalization and robustness in modern deep learning

Maksym Andriushchenko

In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

EPFL2024

Development of a Robotic Microsurgeon for Embryonic Research

Ece Özelçi

Understanding how biological matter takes its shape is instrumental to biology, bioengineering, medicine, and bioinspired engineering. Gaining information on the principles of morphogenesis could enable clinicians to correct developmental abnormalities, ev ...

EPFL2023

Colloidal self-assembly of soft neural interfaces from injectable photovoltaic microdevices

Mahmut Selman Sakar, Zhangjun Huang, Murat Kaynak, Haiyan Jia

Biomimetic retinas with a wide field of view and high resolution are in demand for neuroprosthetics and robot vision. Conventional neural prostheses are manufactured outside the application area and implanted as a complete device using invasive surgery. He ...

2023

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Leonardo Petrini

Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...

EPFL2023

Transcriptomic data meta-analysis reveals common and injury model specific gene expression changes in the regenerating zebrafish heart

Marius Alexandru Botos Rogozsan

Zebrafish have the capacity to fully regenerate the heart after an injury, which lies in sharp contrast to the irreversible loss of cardiomyocytes after a myocardial infarction in humans. Transcriptomics analysis has contributed to dissect underlying signa ...

Nature Portfolio2023

MULTI-TASK CURRICULUM LEARNING FOR PARTIALLY LABELED DATA

Jiancheng Yang, Stanislav Lukyanenko

Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint lear ...

IEEE2023

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Devavrat Tomar, Seyedbehzad Bozorgtabar

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

IEEE2023

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Transcriptomic data meta-analysis reveals common and injury model specific gene expression changes in the regenerating zebrafish heart

Marius Alexandru Botos Rogozsan

Nature Portfolio2023