Neural Dynamics-Informed Pre-trained Framework for Personalized Brain Functional Network Construction
Fuente:
arXiv
Saved in:
| Main Authors: | Jiang, Hongjie, Tang, Yifei, Wang, Shuqiang |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Blood Glucose Control Via Pre-trained Counterfactual Invertible Neural Networks
by: Jiang, Jingchi, et al.
Published: (2024)
by: Jiang, Jingchi, et al.
Published: (2024)
Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks
by: Zhao, Zhe, et al.
Published: (2024)
by: Zhao, Zhe, et al.
Published: (2024)
Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks
by: Wang, Zhili, et al.
Published: (2023)
by: Wang, Zhili, et al.
Published: (2023)
A Pre-training Framework for Relational Data with Information-theoretic Principles
by: Truong, Quang, et al.
Published: (2025)
by: Truong, Quang, et al.
Published: (2025)
Densely Multiplied Physics Informed Neural Networks
by: Jiang, Feilong, et al.
Published: (2024)
by: Jiang, Feilong, et al.
Published: (2024)
Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck
by: Hoang, Van Thuy, et al.
Published: (2024)
by: Hoang, Van Thuy, et al.
Published: (2024)
COMPOL: A Unified Neural Operator Framework for Scalable Multi-Physics Simulations
by: Sun, Yifei, et al.
Published: (2025)
by: Sun, Yifei, et al.
Published: (2025)
Implicit Hypergraph Neural Networks: A Stable Framework for Higher-Order Relational Learning with Provable Guarantees
by: Li, Xiaoyu, et al.
Published: (2025)
by: Li, Xiaoyu, et al.
Published: (2025)
GeoDynamics: A Geometric State-Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds
by: Dan, Tingting, et al.
Published: (2026)
by: Dan, Tingting, et al.
Published: (2026)
Graph Generative Pre-trained Transformer
by: Chen, Xiaohui, et al.
Published: (2025)
by: Chen, Xiaohui, et al.
Published: (2025)
Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
by: Ganguly, Abhisek, et al.
Published: (2026)
by: Ganguly, Abhisek, et al.
Published: (2026)
Stylized Structural Patterns for Improved Neural Network Pre-training
by: Salehi, Farnood, et al.
Published: (2025)
by: Salehi, Farnood, et al.
Published: (2025)
MIPS: a Multimodal Infinite Polymer Sequence Pre-training Framework for Polymer Property Prediction
by: Wang, Jiaxi, et al.
Published: (2025)
by: Wang, Jiaxi, et al.
Published: (2025)
Trainable Quantum Neural Network for Multiclass Image Classification with the Power of Pre-trained Tree Tensor Networks
by: Murota, Keisuke, et al.
Published: (2025)
by: Murota, Keisuke, et al.
Published: (2025)
Gene Regulatory Network Inference from Pre-trained Single-Cell Transcriptomics Transformer with Joint Graph Learning
by: Kommu, Sindhura, et al.
Published: (2024)
by: Kommu, Sindhura, et al.
Published: (2024)
Mask-PINNs: Mitigating Internal Covariate Shift in Physics-Informed Neural Networks
by: Jiang, Feilong, et al.
Published: (2025)
by: Jiang, Feilong, et al.
Published: (2025)
Complex Physics-Informed Neural Network
by: Si, Chenhao, et al.
Published: (2025)
by: Si, Chenhao, et al.
Published: (2025)
Physics-Informed Neural Networks and Extensions
by: Raissi, Maziar, et al.
Published: (2024)
by: Raissi, Maziar, et al.
Published: (2024)
FGBERT: Function-Driven Pre-trained Gene Language Model for Metagenomics
by: Duan, ChenRui, et al.
Published: (2024)
by: Duan, ChenRui, et al.
Published: (2024)
Modeling COVID-19 Dynamics in German States Using Physics-Informed Neural Networks
by: Rothenbeck, Phillip, et al.
Published: (2025)
by: Rothenbeck, Phillip, et al.
Published: (2025)
Pre-training Graph Neural Networks on 2D and 3D Molecular Structures by using Multi-View Conditional Information Bottleneck
by: Hoang, Van Thuy, et al.
Published: (2025)
by: Hoang, Van Thuy, et al.
Published: (2025)
Utilizing Strategic Pre-training to Reduce Overfitting: Baguan -- A Pre-trained Weather Forecasting Model
by: Niu, Peisong, et al.
Published: (2025)
by: Niu, Peisong, et al.
Published: (2025)
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
by: Wang, Zecheng, et al.
Published: (2023)
by: Wang, Zecheng, et al.
Published: (2023)
Exploring Subnetwork Interactions in Heterogeneous Brain Network via Prior-Informed Graph Learning
by: Liu, Siyu, et al.
Published: (2026)
by: Liu, Siyu, et al.
Published: (2026)
Real-Time 2D Temperature Field Prediction in Metal Additive Manufacturing Using Physics-Informed Neural Networks
by: Sajadi, Pouyan, et al.
Published: (2024)
by: Sajadi, Pouyan, et al.
Published: (2024)
OSF: On Pre-training and Scaling of Sleep Foundation Models
by: Shuai, Zitao, et al.
Published: (2026)
by: Shuai, Zitao, et al.
Published: (2026)
SCDM: Unified Representation Learning for EEG-to-fNIRS Cross-Modal Generation in MI-BCIs
by: Li, Yisheng, et al.
Published: (2024)
by: Li, Yisheng, et al.
Published: (2024)
NetFlowGen: Leveraging Generative Pre-training for Network Traffic Dynamics
by: Zhou, Jiawei, et al.
Published: (2024)
by: Zhou, Jiawei, et al.
Published: (2024)
Interpretable Neural Networks with Random Constructive Algorithm
by: Nan, Jing, et al.
Published: (2023)
by: Nan, Jing, et al.
Published: (2023)
Pre-trained Molecular Language Models with Random Functional Group Masking
by: Peng, Tianhao, et al.
Published: (2024)
by: Peng, Tianhao, et al.
Published: (2024)
Integrating Pre-trained Language Model into Neural Machine Translation
by: Hwang, Soon-Jae, et al.
Published: (2023)
by: Hwang, Soon-Jae, et al.
Published: (2023)
A General Benchmark Framework is Dynamic Graph Neural Network Need
by: Zhang, Yusen
Published: (2024)
by: Zhang, Yusen
Published: (2024)
GradINN: Gradient Informed Neural Network
by: Aglietti, Filippo, et al.
Published: (2024)
by: Aglietti, Filippo, et al.
Published: (2024)
Proximity-Informed Calibration for Deep Neural Networks
by: Xiong, Miao, et al.
Published: (2023)
by: Xiong, Miao, et al.
Published: (2023)
Revisiting Heat Flux Analysis of Tungsten Monoblock Divertor on EAST using Physics-Informed Neural Network
by: Wang, Xiao, et al.
Published: (2025)
by: Wang, Xiao, et al.
Published: (2025)
SuPreME: A Supervised Pre-training Framework for Multimodal ECG Representation Learning
by: Cai, Mingsheng, et al.
Published: (2025)
by: Cai, Mingsheng, et al.
Published: (2025)
From Bias to Behavior: Learning Bull-Bear Market Dynamics with Contrastive Modeling
by: Luo, Xiaotong, et al.
Published: (2025)
by: Luo, Xiaotong, et al.
Published: (2025)
Leveraging Influence Functions for Resampling Data in Physics-Informed Neural Networks
by: Naujoks, Jonas R., et al.
Published: (2025)
by: Naujoks, Jonas R., et al.
Published: (2025)
Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator
by: Luo, Beier, et al.
Published: (2025)
by: Luo, Beier, et al.
Published: (2025)
PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection
by: Dai, Enyan, et al.
Published: (2024)
by: Dai, Enyan, et al.
Published: (2024)
Similar Items
-
Blood Glucose Control Via Pre-trained Counterfactual Invertible Neural Networks
by: Jiang, Jingchi, et al.
Published: (2024) -
Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks
by: Zhao, Zhe, et al.
Published: (2024) -
Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks
by: Wang, Zhili, et al.
Published: (2023) -
A Pre-training Framework for Relational Data with Information-theoretic Principles
by: Truong, Quang, et al.
Published: (2025) -
Densely Multiplied Physics Informed Neural Networks
by: Jiang, Feilong, et al.
Published: (2024)