Papers Network Identification
“Network Identification” 태그가 달린 논문 23편 · 필터 해제
BrainSymphony: A Transformer-Driven Fusion of fMRI Time Series and Structural Connectivity
Existing foundation models for neuroimaging are often prohibitively large and data-intensive. We introduce BrainSymphony, a lightweight, parameter-efficient foundation model that achieves state-of-the-art performance whi…
Diffusion MRINetwork IdentificationTime SeriesKoopman operator based identification of nonlinear networks
In this work, we develop a method to identify continuous-time nonlinear networked dynamics via the Koopman operator framework. The proposed technique consists of two steps: the first step identifies the neighbors of each…
Network IdentificationImproved Background Estimation for Gas Plume Identification in Hyperspectral Images
Longwave infrared (LWIR) hyperspectral imaging can be used for many tasks in remote sensing, including detecting and identifying effluent gases by LWIR sensors on airborne platforms. Once a potential plume has been detec…
Network IdentificationFunctional Brain Network Identification in Opioid Use Disorder Using Machine Learning Analysis of Resting-State fMRI BOLD Signals
Understanding the neurobiology of opioid use disorder (OUD) using resting-state functional magnetic resonance imaging (rs-fMRI) may help inform treatment strategies to improve patient outcomes. Recent literature suggests…
Functional ConnectivityNetwork IdentificationDeep Neural Network Identification of Limnonectes Species and New Class Detection Using Image Data
As is true of many complex tasks, the work of discovering, describing, and understanding the diversity of life on Earth (viz., biological systematics and taxonomy) requires many tools. Some of this work can be accomplish…
Network IdentificationOut of Distribution (OOD) DetectionUnique Brain Network Identification Number for Parkinson's Individuals Using Structural MRI
We propose a novel algorithm called Unique Brain Network Identification Number, UBNIN for encoding the brain networks of individual subjects. To realize this objective, we employed structural MRI on 180 Parkinsons diseas…
ClusteringNetwork IdentificationExpand-and-Cluster: Parameter Recovery of Neural Networks
Can we identify the weights of a neural network by probing its input-output mapping? At first glance, this problem seems to have many solutions because of permutation, overparameterisation and activation function symmetr…
Network IdentificationTractable Identification of Electric Distribution Networks
The identification of distribution network topology and parameters is a critical problem that lays the foundation for improving network efficiency, enhancing reliability, and increasing its capacity to host distributed e…
Computational EfficiencyNetwork IdentificationExploring latent networks in resting-state fMRI using voxel-to-voxel causal modeling feature selection
Functional networks characterize the coordinated neural activity observed by functional neuroimaging. The prevalence of different networks during resting state periods provide useful features for predicting the trajector…
feature selectionNetwork IdentificationOn Neural Network Identification for Low-Speed Ship Maneuvering Model
Several studies on ship maneuvering models have been conducted using captive model tests or computational fluid dynamics (CFD) and physical models, such as the maneuvering modeling group (MMG) model. A new system identif…
Network IdentificationA scalable multi-step least squares method for network identification with unknown disturbance topology
Identification methods for dynamic networks typically require prior knowledge of the network and disturbance topology, and often rely on solving poorly scalable non-convex optimization problems. While methods for estimat…
Experimental DesignNetwork IdentificationA frequency domain approach for local module identification in dynamic networks
In classical approaches of dynamic network identification, in order to identify a system (module) embedded in a dynamic network, one has to formulate a Multi-input-Single-output (MISO) identification problem that require…
Network IdentificationUnsupervised deep learning for individualized brain functional network identification
A novel unsupervised deep learning method is developed to identify individual-specific large scale brain functional networks (FNs) from resting-state fMRI (rsfMRI) in an end-to-end learning fashion. Our method leverages …
DecoderDeep LearningNetwork IdentificationRepresentation LearningData-driven distributed control: Virtual reference feedback tuning in dynamic networks
In this paper, the problem of synthesizing a distributed controller from data is considered, with the objective to optimize a model-reference control criterion. We establish an explicit ideal distributed controller that …
Network IdentificationOn the Consistency of Maximum Likelihood Estimators for Causal Network Identification
We consider the problem of identifying parameters of a particular class of Markov chains, called Bernoulli Autoregressive (BAR) processes. The structure of any BAR model is encoded by a directed graph. Incoming edges to …
Network IdentificationNetwork Structure Identification from Corrupt Data Streams
Complex networked systems can be modeled as graphs with nodes representing the agents and links describing the dynamic coupling between them. Previous work on network identification has shown that the network structure o…
Network IdentificationBeyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge
Learning the differential statistical dependency network between two contexts is essential for many real-life applications, mostly in the high dimensional low sample regime. In this paper, we propose a novel differential…
Network IdentificationStructured PredictionInsights into Complex Brain Functions Related to Schizophrenia Disorder through Causal Network Analysis
Gene expression represents a fundamental interface between genes and environment in the development and ongoing plasticity of the human organism. Individual differences in gene expression are likely to underpin much of h…
DiversityNetwork IdentificationDeep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed
Real-world face recognition requires an ability to perceive the unique features of an individual face across multiple, variable images. The primate visual system solves the problem of image invariance using cascades of n…
CaricatureFace RecognitionImage-VariationNetwork IdentificationModeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)
Simultaneous modeling of the spatio-temporal variation patterns of brain functional network from 4D fMRI data has been an important yet challenging problem for the field of cognitive neuroscience and medical image analys…
Brain DecodingMedical Image AnalysisNetwork Identification