Saved in:
| Main Authors: | Bazgir, Omid, Wang, Zichen, Park, Ji Won, Hafner, Marc, Lu, James |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.00926 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
by: Liu, Zewen, et al.
Published: (2025)
by: Liu, Zewen, et al.
Published: (2025)
GRASP: Graph Reasoning Agents for Systems Pharmacology with Human-in-the-Loop
by: Bazgir, Omid, et al.
Published: (2025)
by: Bazgir, Omid, et al.
Published: (2025)
Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs
by: Krach, Florian, et al.
Published: (2022)
by: Krach, Florian, et al.
Published: (2022)
Graph Spring Neural ODEs for Link Sign Prediction
by: Rehmann, Andrin, et al.
Published: (2024)
by: Rehmann, Andrin, et al.
Published: (2024)
Efficient, Accurate and Stable Gradients for Neural ODEs
by: McCallum, Sam, et al.
Published: (2024)
by: McCallum, Sam, et al.
Published: (2024)
Beyond Predictions in Neural ODEs: Identification and Interventions
by: Aliee, Hananeh, et al.
Published: (2021)
by: Aliee, Hananeh, et al.
Published: (2021)
Automatic and Structure-Aware Sparsification of Hybrid Neural ODEs
by: Zou, Bob Junyi, et al.
Published: (2025)
by: Zou, Bob Junyi, et al.
Published: (2025)
Graph Fourier Neural ODEs: Modeling Spatial-temporal Multi-scales in Molecular Dynamics
by: Sun, Fang, et al.
Published: (2024)
by: Sun, Fang, et al.
Published: (2024)
Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs
by: Shi, Guangsi, et al.
Published: (2023)
by: Shi, Guangsi, et al.
Published: (2023)
Designing Stable Neural Networks using Convex Analysis and ODEs
by: Sherry, Ferdia, et al.
Published: (2023)
by: Sherry, Ferdia, et al.
Published: (2023)
Neural Jump ODEs as Generative Models
by: Crowell, Robert A., et al.
Published: (2025)
by: Crowell, Robert A., et al.
Published: (2025)
Sumudu Neural Operator for ODEs and PDEs
by: Zelenskiy, Ben, et al.
Published: (2025)
by: Zelenskiy, Ben, et al.
Published: (2025)
Improving Neural ODEs via Knowledge Distillation
by: Chu, Haoyu, et al.
Published: (2022)
by: Chu, Haoyu, et al.
Published: (2022)
Conformalized Link Prediction on Graph Neural Networks
by: Zhao, Tianyi, et al.
Published: (2024)
by: Zhao, Tianyi, et al.
Published: (2024)
An Empirical Investigation of Neural ODEs and Symbolic Regression for Dynamical Systems
by: Ioannou, Panayiotis, et al.
Published: (2026)
by: Ioannou, Panayiotis, et al.
Published: (2026)
Expressivity of Quadratic Neural ODEs
by: Hanson, Joshua, et al.
Published: (2025)
by: Hanson, Joshua, et al.
Published: (2025)
Control Disturbance Rejection in Neural ODEs
by: Bayram, Erkan, et al.
Published: (2025)
by: Bayram, Erkan, et al.
Published: (2025)
Steerable Neural ODEs on Homogeneous Spaces
by: Andersdotter, Emma, et al.
Published: (2026)
by: Andersdotter, Emma, et al.
Published: (2026)
Adaptive Feedforward Gradient Estimation in Neural ODEs
by: Dabounou, Jaouad
Published: (2024)
by: Dabounou, Jaouad
Published: (2024)
Latent Space Energy-based Neural ODEs
by: Cheng, Sheng, et al.
Published: (2024)
by: Cheng, Sheng, et al.
Published: (2024)
EV-PINN: A Physics-Informed Neural Network for Predicting Electric Vehicle Dynamics
by: Lim, Hansol, et al.
Published: (2024)
by: Lim, Hansol, et al.
Published: (2024)
Feedback Favors the Generalization of Neural ODEs
by: Jia, Jindou, et al.
Published: (2024)
by: Jia, Jindou, et al.
Published: (2024)
Enhancing Spectral Graph Neural Networks with LLM-Predicted Homophily
by: Lu, Kangkang, et al.
Published: (2025)
by: Lu, Kangkang, et al.
Published: (2025)
Dynamic Fraud Detection: Integrating Reinforcement Learning into Graph Neural Networks
by: Dong, Yuxin, et al.
Published: (2024)
by: Dong, Yuxin, et al.
Published: (2024)
AD-NODE: Adaptive Dynamics Learning with Neural ODEs for Mobile Robots Control
by: Yu, Shao-Yi, et al.
Published: (2025)
by: Yu, Shao-Yi, et al.
Published: (2025)
Dynamic Link Prediction with Temporally Enhanced Signed Graph Neural Networks
by: Regier, Derek, et al.
Published: (2026)
by: Regier, Derek, et al.
Published: (2026)
Homotopy-based training of NeuralODEs for accurate dynamics discovery
by: Ko, Joon-Hyuk, et al.
Published: (2022)
by: Ko, Joon-Hyuk, et al.
Published: (2022)
Holomorphic Neural ODEs with Kolmogorov-Arnold Networks for Interpretable Discovery of Complex Dynamics
by: Karn, Bhaskar Ranjan, et al.
Published: (2026)
by: Karn, Bhaskar Ranjan, et al.
Published: (2026)
Simulation-Free Training of Neural ODEs on Paired Data
by: Kim, Semin, et al.
Published: (2024)
by: Kim, Semin, et al.
Published: (2024)
Equivariant Manifold Neural ODEs and Differential Invariants
by: Andersdotter, Emma, et al.
Published: (2024)
by: Andersdotter, Emma, et al.
Published: (2024)
Self-supervised Adversarial Purification for Graph Neural Networks
by: Lee, Woohyun, et al.
Published: (2026)
by: Lee, Woohyun, et al.
Published: (2026)
From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks
by: Cipriani, Cristina, et al.
Published: (2023)
by: Cipriani, Cristina, et al.
Published: (2023)
LOBSTUR: A Local Bootstrap Framework for Tuning Unsupervised Representations in Graph Neural Networks
by: Jeong, So Won, et al.
Published: (2025)
by: Jeong, So Won, et al.
Published: (2025)
Similarity-Navigated Conformal Prediction for Graph Neural Networks
by: Song, Jianqing, et al.
Published: (2024)
by: Song, Jianqing, et al.
Published: (2024)
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer
by: Pengmei, Zihan, et al.
Published: (2024)
by: Pengmei, Zihan, et al.
Published: (2024)
Graph-based Integrated Gradients for Explaining Graph Neural Networks
by: Simpson, Lachlan, et al.
Published: (2025)
by: Simpson, Lachlan, et al.
Published: (2025)
SSTODE: Ocean-Atmosphere Physics-Informed Neural ODEs for Sea Surface Temperature Prediction
by: Jiang, Zheng, et al.
Published: (2025)
by: Jiang, Zheng, et al.
Published: (2025)
ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence
by: Mei, Wenjie, et al.
Published: (2024)
by: Mei, Wenjie, et al.
Published: (2024)
Learning Chaotic Systems and Long-Term Predictions with Neural Jump ODEs
by: Krach, Florian, et al.
Published: (2024)
by: Krach, Florian, et al.
Published: (2024)
Graph Neural Networks with a Distribution of Parametrized Graphs
by: Lee, See Hian, et al.
Published: (2023)
by: Lee, See Hian, et al.
Published: (2023)
Similar Items
-
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
by: Liu, Zewen, et al.
Published: (2025) -
GRASP: Graph Reasoning Agents for Systems Pharmacology with Human-in-the-Loop
by: Bazgir, Omid, et al.
Published: (2025) -
Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs
by: Krach, Florian, et al.
Published: (2022) -
Graph Spring Neural ODEs for Link Sign Prediction
by: Rehmann, Andrin, et al.
Published: (2024) -
Efficient, Accurate and Stable Gradients for Neural ODEs
by: McCallum, Sam, et al.
Published: (2024)