Saved in:
| Main Authors: | Zhang, Yi, Zhang, Zhikun, Wang, Xiangjun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.05990 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Parameter Identification for Partial Differential Equation with Jump Discontinuities in Coefficients by Markov Switching Model and Physics-Informed Machine Learning
by: Zhang, Zhikun, et al.
Published: (2025)
by: Zhang, Zhikun, et al.
Published: (2025)
Residual-loss Anomaly Analysis of Physics-Informed Neural Networks: An Inverse Method for Change-point Detection in Nonlinear Dynamical Systems with Regime Switching
by: Bai, Yuhe, et al.
Published: (2026)
by: Bai, Yuhe, et al.
Published: (2026)
Reconstruction and Prediction of Volterra Integral Equations Driven by Gaussian Noise
by: Xu, Zhihao, et al.
Published: (2025)
by: Xu, Zhihao, et al.
Published: (2025)
Machine Learning for Complex Systems with Abnormal Pattern by Exception Maximization Outlier Detection Method
by: Zhang, Zhikun, et al.
Published: (2024)
by: Zhang, Zhikun, et al.
Published: (2024)
Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential Equations
by: Li, Zhaohui, et al.
Published: (2022)
by: Li, Zhaohui, et al.
Published: (2022)
Solving Fokker-Planck-Kolmogorov Equation by Distribution Self-adaptation Normalized Physics-informed Neural Networks
by: Zhang, Yi, et al.
Published: (2025)
by: Zhang, Yi, et al.
Published: (2025)
Feasibility-Aware Pessimistic Estimation: Toward Long-Horizon Safety in Offline RL
by: Tao, Zhikun
Published: (2025)
by: Tao, Zhikun
Published: (2025)
Long-time Integration of Nonlinear Wave Equations with Neural Operators
by: Lei, Guanhang, et al.
Published: (2024)
by: Lei, Guanhang, et al.
Published: (2024)
Pathway to $O(\sqrt{d})$ Complexity bound under Wasserstein metric of flow-based models
by: Meng, Xiangjun, et al.
Published: (2025)
by: Meng, Xiangjun, et al.
Published: (2025)
From Observations to Parameters: Detecting Changepoint in Nonlinear Dynamics with Simulation-based Inference
by: Deng, Xiangbo, et al.
Published: (2025)
by: Deng, Xiangbo, et al.
Published: (2025)
S'MoRE: Structural Mixture of Residual Experts for Parameter-Efficient LLM Fine-tuning
by: Zeng, Hanqing, et al.
Published: (2025)
by: Zeng, Hanqing, et al.
Published: (2025)
Improve the Fitting Accuracy of Deep Learning for the Nonlinear Schrödinger Equation Using Linear Feature Decoupling Method
by: Zhang, Yunfan, et al.
Published: (2024)
by: Zhang, Yunfan, et al.
Published: (2024)
Spatiotemporal Attention-Augmented Inverse Reinforcement Learning for Multi-Agent Task Allocation
by: Yin, Huilin, et al.
Published: (2025)
by: Yin, Huilin, et al.
Published: (2025)
Advancing Counterfactual Inference through Nonlinear Quantile Regression
by: Xie, Shaoan, et al.
Published: (2023)
by: Xie, Shaoan, et al.
Published: (2023)
Unsupervised Learning Method for the Wave Equation Based on Finite Difference Residual Constraints Loss
by: Feng, Xin, et al.
Published: (2024)
by: Feng, Xin, et al.
Published: (2024)
WENDy for Nonlinear-in-Parameters ODEs
by: Rummel, Nic, et al.
Published: (2025)
by: Rummel, Nic, et al.
Published: (2025)
Bayesian Nonlinear PDE Inference via Gaussian Process Collocation with Application to the Richards Equation
by: Yang, Yumo, et al.
Published: (2025)
by: Yang, Yumo, et al.
Published: (2025)
Asymptotic Time-Uniform Inference for Parameters in Averaged Stochastic Approximation
by: Xie, Chuhan, et al.
Published: (2024)
by: Xie, Chuhan, et al.
Published: (2024)
Consistent Estimation of Numerical Distributions under Local Differential Privacy by Wavelet Expansion
by: Zhao, Puning, et al.
Published: (2025)
by: Zhao, Puning, et al.
Published: (2025)
When Good Equations Get Bad Scores: Improving Symbolic Regression Through Better Parameter Optimization
by: Wang, Boxiao, et al.
Published: (2026)
by: Wang, Boxiao, et al.
Published: (2026)
Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States
by: Cao, Long, et al.
Published: (2024)
by: Cao, Long, et al.
Published: (2024)
Sustainable LLM Inference using Context-Aware Model Switching
by: Yuvarani, et al.
Published: (2026)
by: Yuvarani, et al.
Published: (2026)
Deep Switching State Space Model (DS$^3$M) for Nonlinear Time Series Forecasting with Regime Switching
by: Xu, Xiuqin, et al.
Published: (2021)
by: Xu, Xiuqin, et al.
Published: (2021)
Do Parameters Reveal More than Loss for Membership Inference?
by: Suri, Anshuman, et al.
Published: (2024)
by: Suri, Anshuman, et al.
Published: (2024)
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference
by: Huang, Xunpeng, et al.
Published: (2024)
by: Huang, Xunpeng, et al.
Published: (2024)
Foundation Inference Models for Ordinary Differential Equations
by: Mauel, Maximilian, et al.
Published: (2026)
by: Mauel, Maximilian, et al.
Published: (2026)
Dimension-reduced Reconstruction Map Learning for Parameter Estimation in Likelihood-Free Inference Problems
by: Zhang, Rui, et al.
Published: (2024)
by: Zhang, Rui, et al.
Published: (2024)
Policy Dispersion in Non-Markovian Environment
by: Qu, Bohao, et al.
Published: (2023)
by: Qu, Bohao, et al.
Published: (2023)
Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems
by: Anderka, Rafael, et al.
Published: (2024)
by: Anderka, Rafael, et al.
Published: (2024)
Convergence of Two-Timescale Markovian Stochastic Approximations with Applications in Reinforcement Learning
by: Mahadevan, Vagul, et al.
Published: (2026)
by: Mahadevan, Vagul, et al.
Published: (2026)
Frequency Switching Mechanism for Parameter-E!cient Multi-Task Learning
by: Liu, Shih-Wen, et al.
Published: (2026)
by: Liu, Shih-Wen, et al.
Published: (2026)
Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codes
by: Mi, Xiangjun, et al.
Published: (2025)
by: Mi, Xiangjun, et al.
Published: (2025)
Wave-PDE Nets: Trainable Wave-Equation Layers as an Alternative to Attention
by: Vejendla, Harshil
Published: (2025)
by: Vejendla, Harshil
Published: (2025)
Adaptive Epsilon Adversarial Training for Robust Gravitational Wave Parameter Estimation Using Normalizing Flows
by: Yang, Yiqian, et al.
Published: (2024)
by: Yang, Yiqian, et al.
Published: (2024)
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
by: Hung, Yu-Heng, et al.
Published: (2025)
by: Hung, Yu-Heng, et al.
Published: (2025)
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
by: Liu, Shuze Daniel, et al.
Published: (2024)
by: Liu, Shuze Daniel, et al.
Published: (2024)
Auto-FlexSwitch: Efficient Dynamic Model Merging via Learnable Task Vector Compression
by: Gao, Junqi, et al.
Published: (2026)
by: Gao, Junqi, et al.
Published: (2026)
$S^2$NeRF: Privacy-preserving Training Framework for NeRF
by: Zhang, Bokang, et al.
Published: (2024)
by: Zhang, Bokang, et al.
Published: (2024)
Parameter Inference via Differentiable Diffusion Bridge Importance Sampling
by: Boserup, Nicklas, et al.
Published: (2024)
by: Boserup, Nicklas, et al.
Published: (2024)
Scalable Bayesian Inference for Nonlinear Conservation Laws
by: Weiland, Tim, et al.
Published: (2026)
by: Weiland, Tim, et al.
Published: (2026)
Similar Items
-
Parameter Identification for Partial Differential Equation with Jump Discontinuities in Coefficients by Markov Switching Model and Physics-Informed Machine Learning
by: Zhang, Zhikun, et al.
Published: (2025) -
Residual-loss Anomaly Analysis of Physics-Informed Neural Networks: An Inverse Method for Change-point Detection in Nonlinear Dynamical Systems with Regime Switching
by: Bai, Yuhe, et al.
Published: (2026) -
Reconstruction and Prediction of Volterra Integral Equations Driven by Gaussian Noise
by: Xu, Zhihao, et al.
Published: (2025) -
Machine Learning for Complex Systems with Abnormal Pattern by Exception Maximization Outlier Detection Method
by: Zhang, Zhikun, et al.
Published: (2024) -
Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential Equations
by: Li, Zhaohui, et al.
Published: (2022)