Publications associées à Neuromorphic Architecture with 1M Memristive Synapses for Detection of Weakly Correlated Inputs

Publications associées (35)

Characterization of Machine Learning-Based Surrogate Models of Neural Activation Under Electrical Stimulation

Bioelectromagnetics published by Wiley Periodicals LLC on behalf of Bioelectromagnetics Society.Electrical stimulation of peripheral nerves via implanted electrodes has been shown to be a promising approach to restore sensation, movement, and autonomic fun ...

2025

Leaf Level Ash Dieback Disease Detection and Online Severity Estimation With UAVs

Mirko Kovac

Ash dieback, caused by the fungal pathogen Hymenoscyphus fraxineus, is devastating ash tree populations across U.K. and Europe, with projections indicating that up to 80% of ash trees may die as a result of the disease. The extensive loss of this keystone ...

2025

Boosting Protein Graph Representations through Static-Dynamic Fusion

Pengkang Guo, Pierre Vandergheynst, Bruno Emanuel Ferreira De Sousa Correia, Daniel Probst

Machine learning for protein modeling faces significant challenges due to proteins' inherently dynamic nature, yet most graph-based machine learning methods rely solely on static structural information. Recently, the growing availability of molecular dynam ...

2025

A clinical road map for single-cell omics

Grégoire Courtine, Jocelyne Bloch

In a matter of years, single-cell omics has matured from a pioneering technique employed by just a handful of specialized laboratories to become a ubiquitous feature of biological research and a key driver of scientific discovery. The widespread adoption a ...

2025

Partial discharge localization in power transformer tanks using machine learning methods

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Nature Publishing Group2024

Weak correlations between visual abilities in healthy older adults, despite long-term performance stability

Michael Herzog, Simona Adele Garobbio

Using batteries of visual tests, most studies have found that there are only weak correlations between the performance levels of the tests. Factor analysis has confirmed these results. This means that a participant excelling in one test may rank low in ano ...

2024

Novel theory and potential applications of central diastolic pressure decay time constant

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Central aortic diastolic pressure decay time constant ( ) is according to the two-element Windkessel model equal to the product of total peripheral resistance (R) times total arterial compliance (C ). As such, it is related to arterial stiffness, which has ...

2024

A bistable inhibitory optoGPCR for multiplexed optogenetic control of neural circuits

Mauro Pulin

Information is transmitted between brain regions through the release of neurotransmitters from long-range projecting axons. Understanding how the activity of such long-range connections contributes to behavior requires efficient methods for reversibly mani ...

Nature Publishing Group2024

Quantitative T2 Mapping of Acute Pancreatitis

Tom Hilbert

Background: Quantification of the T2 signal by means of T2 mapping in acute pancreatitis (AP) has the potential to quantify the parenchymal edema. Quantitative T2 mapping may overcome the limitations of previously reported scoring systems for reliable asse ...

Wiley2024

The hindbrain and cortico-reticular pathway in adolescent idiopathic scoliosis

Bénédicte Marie Maréchal

AIM: To characterise the corticoreticular pathway (CRP) in a case -control cohort of adolescent idiopathic scoliosis (AIS) patients using high -resolution slice -accelerated readoutsegmented echo -planar diffusion tensor imaging (DTI) to enhance the discri ...

W B Saunders Co Ltd2024

Simplification of spiking neural network models

Wulfram Gerstner, Henry Markram, Eilif Benjamin Muller, James Gonzalo King, Christian Antonio Pozzorini, Csaba Erö, Christian Andreas Rössert, Idan Segev, Willem Anna Mark Wybo

The simplification of neural network models is described. For example, a method for simplifying a neural network model includes providing the neural network model to be simplified, defining a first temporal filter for the conveyance of input from a neuron ...

2024

On the implementation of nonlinearities in optical neural networks: opinion

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç, Ilker Oguz, Mustafa Yildirim

Optical neural networks are expected to be hybrid systems for the foreseeable future combining optics and electronics. The linear portion of the system, consisting of the weighted interconnections between the neurons, can be realized optically. The nonline ...

Optica Publishing Group2024

Influence of Ventilation on Formation and Growth of 1-20 nm Particles via Ozone-Human Chemistry

Dusan Licina, Shen Yang, Marouane Merizak, Meixia Zhang

Ozone reaction with human surfaces is an important source of ultrafine particles indoors. However, 1-20 nm particles generated from ozone-human chemistry, which mark the first step of particle formation and growth, remain understudied. Ventilation and indo ...

Amer Chemical Soc2024

Transfer learning in robotics: An upcoming breakthrough? A review of promises and challenges

Aude Billard, Kunpeng Yao, Bernardo Fichera

Transfer learning is a conceptually-enticing paradigm in pursuit of truly intelligent embodied agents. The core concept—reusing prior knowledge to learn in and from novel situations—is successfully leveraged by humans to handle novel situations. In recent ...

SAGE Publications2024

Principles of Network Plasticity in Neocortical Microcircuits

András Ecker

Synaptic plasticity underlies our ability to learn and adapt to the constantly changing environment. The phenomenon of synapses changing their efficacy in an activity-dependent manner is often studied in small groups of neurons in vitro or indirectly throu ...

EPFL2023

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Eilif Benjamin Muller, Michael Reimann, Marwan Muhammad Ahmed Abdellah, James Gonzalo King, András Ecker, Pramod Shivaji Kumbhar, Giuseppe Chindemi, Daniela Egas Santander, James Bryden Isbister, Ioannis Magkanaris, Sirio Bolaños Puchet, Jorge Blanco Alonso

Synaptic plasticity underlies the brain’s ability to learn and adapt. While experiments in brain slices have revealed mechanisms and protocols for the induction of plasticity between pairs of neurons, how these synaptic changes are coordinated in biologica ...

2024

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Kynthia Chamilothori, Seungryong Kim, Bahar Aydemir

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

Towards a multiscale point cloud structural similarity metric

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

IEEE2023

Engram cell connectivity as a mechanism for information encoding and memory function

Maurizio Ferdinando Pezzoli

Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, which allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here, we test the h ...

Cell Press2023