Publication

Supervised learning to quantify amyloidosis in whole brains of an Alzheimer's disease mouse model acquired with optical projection tomography

Publications associées (30)

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Giuseppe Carleo, Filippo Vicentini, Riccardo Rossi, Clemens Giuliani

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by using kernel me ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2023

Brain mitochondrial diversity and network organization predict anxiety-like behavior in male mice

Maria del Carmen Sandi Perez

The brain and behavior are under energetic constraints, limited by mitochondrial energy transformation capacity. However, the mitochondria-behavior relationship has not been systematically studied at a brain-wide scale. Here we examined the association bet ...

Nature Research2023

A structured prediction approach for robot imitation learning

Aude Billard, Iason Batzianoulis, Anqing Duan

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised le ...

Sage Publications Ltd2023

Revealing the complexity of ultra-soft hydrogel re-swelling inside the brain

Stéphanie Lacour, Michael Shur, John Martin Kolinski, Outman Akouissi, Olivier Didier Christian Rizzo

The brain is an ultra-soft viscoelastic matrix. Sub-kPa hydrogels match the brain's mechanical properties but are challenging to manipulate in an implantable format. We propose a simple fabrication and processing sequence, consisting of de-hydration, patte ...

2023

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

Max Stieber, Martin Weigert, Benjamin Tobias Gallusser

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

Springer International Publishing Ag2023

Correlative light and volume electron microscopy to study brain development

Graham Knott

Recent advances in volume electron microscopy (EM) have been driving our thorough understanding of the brain architecture. Volume EM becomes increasingly powerful when cells and their subcellular structures that are imaged in light microscopy are correlate ...

OXFORD UNIV PRESS2023

Supervised learning and inference of spiking neural networks with temporal coding

Ana Stanojevic

The way biological brains carry out advanced yet extremely energy efficient signal processing remains both fascinating and unintelligible. It is known however that at least some areas of the brain perform fast and low-cost processing relying only on a smal ...

EPFL2023

Cortical alterations after very preterm birth and the association with socio-emotional abilities from childhood to early adolescence

Jean-Philippe Thiran, Elda Fischi Gomez, Vanessa Siffredi

Very preterm birth (VPT;

2023

Mechanism of KRAS-driven T cell infiltration in colorectal cancer

Amber Dawn Bowler

Colorectal cancer is the second-leading cause of cancer death worldwide. Early-stage disease can be detected with preventative medical screening and is treatable with surgical resection. Sixty-percent of patients, however, are diagnosed with advanced-stage ...

EPFL2023

A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

David Atienza Alonso, Lara Orlandic, Tomas Teijeiro Campo

Background and Objective: Cough audio signal classification is a potentially useful tool in screening for respiratory disorders, such as COVID-19. Since it is dangerous to collect data from patients with contagious diseases, many research teams have turned ...

2023