Concept
Gaz neuronal
Publications associées (22)
Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining
Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...
New York2023Information-Driven Gas Distribution Mapping for Autonomous Mobile Robots
Alcherio Martinoli, Chiara Ercolani, Faezeh Rahbar
The ability to sense airborne pollutants with mobile robots provides a valuable asset for domains such as industrial safety and environmental monitoring. Oftentimes, this involves detecting how certain gases are spread out in the environment, commonly refe ...
MDPI20234M: Massively Multimodal Masked Modeling
Shuqing Teresa Yeo, Amir Roshan Zamir, Oguzhan Fatih Kar, Roman Christian Bachmann, David Mizrahi
Current machine learning models for vision are often highly specialized and limited to a single modality and task. In contrast, recent large language models exhibit a wide range of capabilities, hinting at a possibility for similarly versatile models in co ...
Neural Information Processing Systems (Nips)2023A novel recursive algorithm used to model hardware programmable neighborhood mechanism of self-organizing neural networks
In this paper we propose a novel recursive algorithm that models the neighborhood mechanism, which is commonly used in self-organizing neural networks (NNs). The neighborhood can be viewed as a map of connections between particular neurons in the NN. Its r ...
Elsevier2015Organizing neural networks
Henry Markram, Rodrigo de Campos Perin, Thomas Berger
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by betwe ...
2011An influence of current-leakage in analog memory on training Kohonen neural network implemented on silicon
The paper presents how the current leakage encountered in capacitive analog memories affects the learning process of hardware implemented Kohonen neural networks (KNN). MOS transistor leakage currents, which strongly depend on temperature, increase the net ...
2010Realization of the Conscience Mechanism in CMOS Implementation of Winner-Takes-All Self-Organizing Neural Networks
This paper presents a complementary metal–oxide– semiconductor (CMOS) implementation of a conscience mechanism used to improve the effectiveness of learning in the winnertakes- all (WTA) artificial neural networks (ANNs) realized at the transistor level. T ...
Institute of Electrical and Electronics Engineers2010A New Fast Training Algorithm of the WTM Kohonen Neural Network Implemented for Classification of Biomedical Signals
A new optimized algorithm for the learning process suitable for hardware implemented Winner Takes Most Kohonen Neural Network (KNN) has been proposed in the paper. In networks of this type a neighborhood mechanism is used to improve the convergence propert ...
2009New Fast Training Algorithm Suitable For Hardware Kohonen Neural Networks Designed For Analysis Of Biomedical Signals
A new optimized algorithm for the learning process suitable for hardware implemented Winner Takes Most Kohonen Neural Network (KNN) has been proposed in the paper. In networks of this type a neighborhood mechanism is used to improve the convergence propert ...
Insticc-Inst Syst Technologies Information Control & Communication, Avenida D Manuel L, 27A 2 Esquerdo, Setubal, 2910-595, Portugal2009SOM-based Clustering of Multilingual Documents Using an Ontology
Clustering similar documents is a difficult task for text data mining. Difficulties stem especially from the way documents are translated into numerical vectors. In this chapter, we will present a method that uses Self Organizing Map (SOM) to cluster medic ...
Information Science Reference2008