Ting-TingGao / Network-SDE-InferenceLinks
Code and data for paper: Learning interpretable dynamics of stochastic complex systems from experimental data
☆22Updated 3 months ago
Alternatives and similar repositories for Network-SDE-Inference
Users that are interested in Network-SDE-Inference are comparing it to the libraries listed below
Sorting:
- code of ICLR 2024 paper Reinforcement Symbolic Regression Machine☆15Updated last year
- [ICLR 2024] Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data☆67Updated 5 months ago
- ☆14Updated 5 years ago
- ☆24Updated 7 months ago
- Neural ODE Processes for Network Dynamics (NDP4ND), a new class of stochastic processes governed by stochastic data-adaptive network dyna…☆14Updated last year
- [NeurIPS 23] Official Code for "Learning Efficient Surrogate Dynamic Models with Graph Spline Networks"☆16Updated last year
- Symbolic physics learner: Discovering governing equations via Monte Carlo tree search☆26Updated 2 years ago
- Code for the TMLR 2023 paper "GRAM-ODE: Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting"☆20Updated 2 years ago
- ☆42Updated 3 years ago
- Tackling the Curse of Dimensionality with Physics-Informed Neural Networks☆15Updated last year
- Generalizing to New Physical Systems via Context-Informed Dynamics Model☆26Updated last year
- Multiwavelets-based operator model☆69Updated 3 years ago
- Physics-incorporated Graph Neural Network Using Dynamic Higher-Order Spatio-temporal Graphs for Multivariate Time Series Imputation☆16Updated 5 months ago
- Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"☆76Updated 2 years ago
- Benchmarking of diffusion models for global field reconstruction from sparse observations☆29Updated last year
- ☆17Updated last year
- Stochastic Physics-Informed Neural Ordinary Differential Equations☆19Updated 3 years ago
- Collection of resources about partial differential equations, graph neural networks, deep learning and dynamical system simulation☆96Updated 3 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- [NeurIPS 2024] Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling☆25Updated 7 months ago
- This repo provides some examples (mostly solving PDE) to compare KAN and MLP☆19Updated last year
- Higher-order Granger reservoir computing☆26Updated last year
- [NeurIPS2024] DiffPhyCon uses generative models to control complex physical systems☆47Updated 3 months ago
- About Code release for “RoPINN: Region Optimized Physics-Informed Neural Networks” (NeurIPS 2024), https://arxiv.org/abs/2405.14369☆60Updated 6 months ago
- Automated Discovery of Interactions and Dynamics for Large Networked Dynamical Systems☆16Updated 4 years ago
- [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values☆30Updated last year
- [NeurIPS 2022] Minimizing L_inf Physics-Informed Loss for PINN with adversarial training☆38Updated 2 years ago
- ☆13Updated last year
- Neural Dynamics on Complex Networks☆55Updated 5 years ago
- Deep identification of symbolic open-form PDEs via enhanced reinforcement-learning☆40Updated last year