Imagen de Portada

A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Yap, Sin-Yee, Loo, Junn Yong, Ting, Chee-Ming, Noman, Fuad, Phan, Raphael C. -W., Razi, Adeel, Dowe, David L.
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Brain-MGF: Multimodal Graph Fusion Network for EEG-fMRI Brain Connectivity Analysis Under Psilocybin
por: Yap, Sin-Yee, et al.
Publicado: (2025)

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification
por: Noman, Fuad, et al.
Publicado: (2021)

T2I-Diff: fMRI Signal Generation via Time-Frequency Image Transform and Classifier-Free Denoising Diffusion Models
por: Tew, Hwa Hui, et al.
Publicado: (2025)

Functional MRI Time Series Generation via Wavelet-Based Image Transform and Spectral Flow Matching for Brain Disorder Identification
por: Tew, Hwa Hui, et al.
Publicado: (2026)

Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling
por: Loo, Junn Yong, et al.
Publicado: (2024)

Dynamic MRI reconstruction using low-rank plus sparse decomposition with smoothness regularization
por: Ting, Chee-Ming, et al.
Publicado: (2024)

SFC-GAN: A Generative Adversarial Network for Brain Functional and Structural Connectome Translation
por: Tan, Yee-Fan, et al.
Publicado: (2025)

A Deep Probabilistic Flow-Based Framework for Unsupervised Cross-Domain Soft Sensing
por: Loo, Junn Yong, et al.
Publicado: (2023)

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing
por: Tew, Hwa Hui, et al.
Publicado: (2025)

KANS: Knowledge Discovery Graph Attention Network for Soft Sensing in Multivariate Industrial Processes
por: Tew, Hwa Hui, et al.
Publicado: (2025)

PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI Slices
por: Kang, Ming, et al.
Publicado: (2024)

BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection
por: Kang, Ming, et al.
Publicado: (2023)

Cross-domain Transfer Learning and State Inference for Soft Robots via a Semi-supervised Sequential Variational Bayes Framework
por: Sapai, Shageenderan, et al.
Publicado: (2023)

CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer
por: Kang, Ming, et al.
Publicado: (2023)

CAFCT-Net: A CNN-Transformer Hybrid Network with Contextual and Attentional Feature Fusion for Liver Tumor Segmentation
por: Kang, Ming, et al.
Publicado: (2024)

Learning Energy-Based Generative Models via Potential Flow: A Variational Principle Approach to Probability Density Homotopy Matching
por: Loo, Junn Yong, et al.
Publicado: (2025)

MDHA: Multi-Scale Deformable Transformer with Hybrid Anchors for Multi-View 3D Object Detection
por: Adeline, Michelle, et al.
Publicado: (2024)

Denoising via Repainting: an image denoising method using layer wise medical image repainting
por: Pal, Arghya, et al.
Publicado: (2025)

A Multimodal Feature Distillation with Mamba-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities
por: Kang, Ming, et al.
Publicado: (2024)

ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation
por: Kang, Ming, et al.
Publicado: (2023)

GSMT: Graph Fusion and Spatiotemporal TaskCorrection for Multi-Bus Trajectory Prediction
por: Ding, Fan, et al.
Publicado: (2025)

Sigma-point Kalman Filter with Nonlinear Unknown Input Estimation via Optimization and Data-driven Approach for Dynamic Systems
por: Loo, Junn Yong, et al.
Publicado: (2023)

BrainSymphony: A parameter-efficient multimodal foundation model for brain dynamics with limited data
por: Khajehnejad, Moein, et al.
Publicado: (2025)

Graph-Based Representation Learning of Neuronal Dynamics and Behavior
por: Khajehnejad, Moein, et al.
Publicado: (2024)

PanopMamba: Vision State Space Modeling for Nuclei Panoptic Segmentation
por: Kang, Ming, et al.
Publicado: (2026)

Riemann Zero Condition Off the Critical Line: A Matrix Formulation
por: Yap, Chee Kian
Publicado: (2024)

Hi-DREAM: Brain Inspired Hierarchical Diffusion for fMRI Reconstruction via ROI Encoder and visuAl Mapping
por: Zhang, Guowei, et al.
Publicado: (2025)

On Predictive planning and counterfactual learning in active inference
por: Paul, Aswin, et al.
Publicado: (2024)

Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications
por: Lu, Yuxing, et al.
Publicado: (2025)

A Principled Bayesian Framework for Training Binary and Spiking Neural Networks
por: Walker, James A., et al.
Publicado: (2025)

Seeing Roads Through Words: A Language-Guided Framework for RGB-T Driving Scene Segmentation
por: Reddy, Ruturaj, et al.
Publicado: (2026)

RAPiD: Real-time Deterministic Trajectory Planning via Diffusion Behavior Priors for Safe and Efficient Autonomous Driving
por: Reddy, Ruturaj, et al.
Publicado: (2026)

Transformer-based Deep Learning Model for Joint Routing and Scheduling with Varying Electric Vehicle Numbers
por: Yap, Jun Kang, et al.
Publicado: (2025)

A Novel Approach to the Initial Value Problem with a complete validated algorithm
por: Zhang, Bingwei, et al.
Publicado: (2025)

Distortion Bounds of Subdivision Models for SO(3)
por: Zhang, Zhaoqi, et al.
Publicado: (2025)

End Cover for Initial Value Problem: Complete Validated Algorithms with Complexity Analysis
por: Zhang, Bingwei, et al.
Publicado: (2026)

Taylor Tube Method for Validated IVP
por: Zhang, Bingwei, et al.
Publicado: (2026)

Joint Optimisation of Electric Vehicle Routing and Scheduling: A Deep Learning-Driven Approach for Dynamic Fleet Sizes
por: Yap, Jun Kang, et al.
Publicado: (2025)

Asian American identity : shared racial status and political context / Jane Junn, Natalie Masuoka
por: Junn, Jane
Publicado: (2004)

Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld
por: Khajehnejad, Moein, et al.
Publicado: (2024)