Implicit Neural Differential Model for Spatiotemporal Dynamics
Fuente:
arXiv
Saved in:
| Main Authors: | Akhare, Deepak, Du, Pan, Luo, Tengfei, Wang, Jian-Xun |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid Neural Modeling
by: Akhare, Deepak, et al.
Published: (2023)
by: Akhare, Deepak, et al.
Published: (2023)
Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification
by: Jantre, Sanket, et al.
Published: (2025)
by: Jantre, Sanket, et al.
Published: (2025)
High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention
by: Akhare, Deepak, et al.
Published: (2026)
by: Akhare, Deepak, et al.
Published: (2026)
Neural Differentiable Modeling with Diffusion-Based Super-resolution for Two-Dimensional Spatiotemporal Turbulence
by: Fan, Xiantao, et al.
Published: (2024)
by: Fan, Xiantao, et al.
Published: (2024)
Automotive Crash Dynamics Modeling Accelerated with Machine Learning
by: Nabian, Mohammad Amin, et al.
Published: (2025)
by: Nabian, Mohammad Amin, et al.
Published: (2025)
On the Spatiotemporal Dynamics of Generalization in Neural Networks
by: Wei, Zichao
Published: (2026)
by: Wei, Zichao
Published: (2026)
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
by: Minartz, Koen, et al.
Published: (2023)
by: Minartz, Koen, et al.
Published: (2023)
GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models through Statistically-Guided Geo-Prototyping
by: An, Bang, et al.
Published: (2024)
by: An, Bang, et al.
Published: (2024)
Neural Point Process for Learning Spatiotemporal Event Dynamics
by: Zhou, Zihao, et al.
Published: (2021)
by: Zhou, Zihao, et al.
Published: (2021)
Global Stress Generation and Spatiotemporal Super-Resolution Physics-Informed Operator under Dynamic Loading for Two-Phase Random Materials
by: Xing, Tengfei, et al.
Published: (2025)
by: Xing, Tengfei, et al.
Published: (2025)
Semi-Implicit Neural Ordinary Differential Equations
by: Zhang, Hong, et al.
Published: (2024)
by: Zhang, Hong, et al.
Published: (2024)
Learning Set Functions with Implicit Differentiation
by: Özcan, Gözde, et al.
Published: (2024)
by: Özcan, Gözde, et al.
Published: (2024)
Using Neural Implicit Flow To Represent Latent Dynamics Of Canonical Systems
by: Nasim, Imran, et al.
Published: (2024)
by: Nasim, Imran, et al.
Published: (2024)
Implicit Hypergraph Neural Network
by: Choudhuri, Akash, et al.
Published: (2025)
by: Choudhuri, Akash, et al.
Published: (2025)
Bridging Dynamic Factor Models and Neural Controlled Differential Equations for Nowcasting GDP
by: Lim, Seonkyu, et al.
Published: (2024)
by: Lim, Seonkyu, et al.
Published: (2024)
Data Diversity as Implicit Regularization: How Does Diversity Shape the Weight Space of Deep Neural Networks?
by: Ba, Yang, et al.
Published: (2024)
by: Ba, Yang, et al.
Published: (2024)
Over-squashing in Spatiotemporal Graph Neural Networks
by: Marisca, Ivan, et al.
Published: (2025)
by: Marisca, Ivan, et al.
Published: (2025)
Neural Spatiotemporal Point Processes: Trends and Challenges
by: Mukherjee, Sumantrak, et al.
Published: (2025)
by: Mukherjee, Sumantrak, et al.
Published: (2025)
Spatiotemporal-Augmented Graph Neural Networks for Human Mobility Simulation
by: Wang, Yu, et al.
Published: (2023)
by: Wang, Yu, et al.
Published: (2023)
Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
by: Naour, Etienne Le, et al.
Published: (2023)
by: Naour, Etienne Le, et al.
Published: (2023)
UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction
by: Yu, Dahai, et al.
Published: (2025)
by: Yu, Dahai, et al.
Published: (2025)
Adaptive Spatiotemporal Augmentation for Improving Dynamic Graph Learning
by: Chu, Xu, et al.
Published: (2025)
by: Chu, Xu, et al.
Published: (2025)
SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields
by: Park, David Keetae, et al.
Published: (2025)
by: Park, David Keetae, et al.
Published: (2025)
G-PARC: Graph-Physics Aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics on Unstructured Meshes
by: Beerman, Jack T., et al.
Published: (2026)
by: Beerman, Jack T., et al.
Published: (2026)
Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction
by: Mi, Yuan, et al.
Published: (2024)
by: Mi, Yuan, et al.
Published: (2024)
Simulation-Free Differential Dynamics through Neural Conservation Laws
by: Hua, Mengjian, et al.
Published: (2025)
by: Hua, Mengjian, et al.
Published: (2025)
Learning Dynamic Graph Embeddings with Neural Controlled Differential Equations
by: Qin, Tiexin, et al.
Published: (2023)
by: Qin, Tiexin, et al.
Published: (2023)
Incident-Guided Spatiotemporal Traffic Forecasting
by: Fan, Lixiang, et al.
Published: (2026)
by: Fan, Lixiang, et al.
Published: (2026)
Unpacking the Implicit Norm Dynamics of Sharpness-Aware Minimization in Tensorized Models
by: Cao, Tianxiao, et al.
Published: (2025)
by: Cao, Tianxiao, et al.
Published: (2025)
Studying the Impact of Latent Representations in Implicit Neural Networks for Scientific Continuous Field Reconstruction
by: Xu, Wei, et al.
Published: (2024)
by: Xu, Wei, et al.
Published: (2024)
On the Implicit Reward Overfitting and the Low-rank Dynamics in RLVR
by: Ye, Hao, et al.
Published: (2026)
by: Ye, Hao, et al.
Published: (2026)
Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models
by: Wu, Hao, et al.
Published: (2025)
by: Wu, Hao, et al.
Published: (2025)
Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models
by: Wang, Runqian, et al.
Published: (2025)
by: Wang, Runqian, et al.
Published: (2025)
Recovering Physical Dynamics from Discrete Observations via Intrinsic Differential Consistency
by: Luo, Yuxiang, et al.
Published: (2026)
by: Luo, Yuxiang, et al.
Published: (2026)
IGN : Implicit Generative Networks
by: Luo, Haozheng, et al.
Published: (2022)
by: Luo, Haozheng, et al.
Published: (2022)
SRNN: Spatiotemporal Relational Neural Network for Intuitive Physics Understanding
by: Yang, Fei
Published: (2025)
by: Yang, Fei
Published: (2025)
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
by: Liu, Shengchao, et al.
Published: (2023)
by: Liu, Shengchao, et al.
Published: (2023)
M-STAR: Multi-Scale Spatiotemporal Autoregression for Human Mobility Modeling
by: Luo, Yuxiao, et al.
Published: (2025)
by: Luo, Yuxiao, et al.
Published: (2025)
AutoSTF: Decoupled Neural Architecture Search for Cost-Effective Automated Spatio-Temporal Forecasting
by: Lyu, Tengfei, et al.
Published: (2024)
by: Lyu, Tengfei, et al.
Published: (2024)
NeuralOGCM: Differentiable Ocean Modeling with Learnable Physics
by: Wu, Hao, et al.
Published: (2025)
by: Wu, Hao, et al.
Published: (2025)
Similar Items
-
DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid Neural Modeling
by: Akhare, Deepak, et al.
Published: (2023) -
Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification
by: Jantre, Sanket, et al.
Published: (2025) -
High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention
by: Akhare, Deepak, et al.
Published: (2026) -
Neural Differentiable Modeling with Diffusion-Based Super-resolution for Two-Dimensional Spatiotemporal Turbulence
by: Fan, Xiantao, et al.
Published: (2024) -
Automotive Crash Dynamics Modeling Accelerated with Machine Learning
by: Nabian, Mohammad Amin, et al.
Published: (2025)