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CLIP the Gap: A Single Domain Generalization Approach for Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain. While this has been well studied for image classification, the literature on SDG object detection remai ...

Ieee Computer Soc2023

Influence of channel geomorphic units on bedload transport and river morphology during low‐magnitude bed‐forming floods coupled with sediment augmentation

Giovanni De Cesare, Severin Stähly, Christian Mörtl, Robin Schroff

In this study, we map different types of channel geomorphic units in a sediment-starved, residual-flow reach before and after an artificial flood. Bedload particles of a previous sediment augmentation measure are tracked with passive integrated transponder ...

2023

Melting pseudosymmetry and thermal expansion in 3-benzoylpropionic acid

Tomasz Poreba

The thermal behavior of 3-benzoylpropionic acid (BPA) was investigated using single-crystal and synchrotron powder X-diffraction, as well as differential scanning calorimetry analysis. The study revealed the existence of two subtly distinct structures of B ...

ROYAL SOC CHEMISTRY2023

Targeting the Progesterone Receptor in Breast Cancer: Mind the Short Form!

Cathrin Brisken, Carlos Henrique Venturi Ronchi

The presurgical window of opportunity trial (WOT) MIPRA provides evidence that neoadjuvant treatment with the prog-esterone receptor (PR) antagonist mifepristone (RU486) may benefit patients with estrogen receptor-positive (ER+) breast cancer characterized ...

AMER ASSOC CANCER RESEARCH2023

Essays in macro-finance and deep learning

Goutham Gopalakrishna

This thesis studies the origins and consequences of financial crises, and computational techniques to solve continuous-time economic models that explain such crises. The first chapter shows that financial recessions are typically characterised by a large ...

EPFL2023

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Silvestro Micera, Michael Lassi

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...

IOP Publishing Ltd2023

Microscopic interplay of temperature and disorder of a one-dimensional elastic interface

Elisabeth Agoritsas, Thierry Giamarchi

Elastic interfaces display scale-invariant geometrical fluctuations at sufficiently large lengthscales. Their asymptotic static roughness then follows a power-law behavior, whose associated exponent provides a robust signature of the universality class to ...

2022

Sense of agency for intracortical brain-machine interfaces

Olaf Blanke, Andrea Serino, Tommaso Enrico Bertoni, Nathan Quentin Faivre, Marco Solcà, Pavo Orepic, Gaurav Sharma

Intracortical brain-machine interfaces decode motor commands from neural signals and translate them into actions, enabling movement for paralysed individuals. The subjective sense of agency associated with actions generated via intracortical brain-machine ...

NATURE PORTFOLIO2022

Selective area epitaxy of GaAs: the unintuitive role of feature size and pitch

Anna Fontcuberta i Morral, Lucas Güniat, Didem Dede, Valerio Piazza, Martin George Friedl, Elif Nur Dayi, Nicholas Paul Morgan, Akshay Balgarkashi, Vladimir Dubrovskii

Selective area epitaxy (SAE) provides the path for scalable fabrication of semiconductor nanostructures in a device-compatible configuration. In the current paradigm, SAE is understood as localized epitaxy, and is modelled by combining planar and self-asse ...

IOP Publishing Ltd2022

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