Copertina

Governing Equation Discovery from Data Based on Differential Invariants

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Hu, Lexiang, Li, Yikang, Lin, Zhouchen
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Explicit Discovery of Nonlinear Symmetries from Dynamic Data
di: Hu, Lexiang, et al.
Pubblicazione: (2025)

Symmetry Discovery for Different Data Types
di: Hu, Lexiang, et al.
Pubblicazione: (2024)

Incorporating Arbitrary Matrix Group Equivariance into KANs
di: Hu, Lexiang, et al.
Pubblicazione: (2024)

Adaptive Global and Fine-Grained Perceptual Fusion for MLLM Embeddings Compatible with Hard Negative Amplification
di: Hu, Lexiang, et al.
Pubblicazione: (2026)

High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces
di: Shao, Shihao, et al.
Pubblicazione: (2024)

Discovering Symbolic Differential Equations with Symmetry Invariants
di: Yang, Jianke, et al.
Pubblicazione: (2025)

DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
di: Chen, Yang, et al.
Pubblicazione: (2024)

Symmetry-Informed Governing Equation Discovery
di: Yang, Jianke, et al.
Pubblicazione: (2024)

Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization
di: Li, Huan, et al.
Pubblicazione: (2021)

Mechanistic PDE Networks for Discovery of Governing Equations
di: Pervez, Adeel, et al.
Pubblicazione: (2025)

Causal Discovery via Quantile Partial Effect
di: Chen, Yikang, et al.
Pubblicazione: (2025)

Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness
di: Sun, Ke, et al.
Pubblicazione: (2021)

Automating the Discovery of Partial Differential Equations in Dynamical Systems
di: Li, Weizhen, et al.
Pubblicazione: (2024)

On the $O(\frac{\sqrt{d}}{K^{1/4}})$ Convergence Rate of AdamW Measured by $\ell_1$ Norm
di: Li, Huan, et al.
Pubblicazione: (2025)

Convergence Rate Analysis of LION
di: Dong, Yiming, et al.
Pubblicazione: (2024)

Convergence Rate Analysis of the AdamW-Style Shampoo: Unifying One-Sided and Two-Sided Preconditioning
di: Li, Huan, et al.
Pubblicazione: (2026)

Beyond likelihood ratio bias: Nested multi-time-scale stochastic approximation for likelihood-free parameter estimation
di: Li, Zehao, et al.
Pubblicazione: (2024)

Dynamic Bayesian Optimization Framework for Instruction Tuning in Partial Differential Equation Discovery
di: Qu, Junqi, et al.
Pubblicazione: (2025)

Data-Driven Self-Supervised Learning for the Discovery of Solution Singularity for Partial Differential Equations
di: Cai, Difeng, et al.
Pubblicazione: (2025)

On Leveraging Unlabeled Data for Concurrent Positive-Unlabeled Classification and Robust Generation
di: Yu, Bing, et al.
Pubblicazione: (2020)

Constrained or Unconstrained? Neural-Network-Based Equation Discovery from Data
di: Norman, Grant, et al.
Pubblicazione: (2024)

Ensemble WSINDy for Data Driven Discovery of Governing Equations from Laser-based Full-field Measurements
di: Schmid, Abigail C., et al.
Pubblicazione: (2024)

A Unified Framework for Simultaneous Parameter and Function Discovery in Differential Equations
di: Manor, Shalev, et al.
Pubblicazione: (2025)

Generative Discovery of Partial Differential Equations by Learning from Math Handbooks
di: Xu, Hao, et al.
Pubblicazione: (2025)

On the Limitations and Capabilities of Position Embeddings for Length Generalization
di: Chen, Yang, et al.
Pubblicazione: (2025)

Attention Sinks Induce Gradient Sinks: Massive Activations as Gradient Regulators in Transformers
di: Chen, Yihong, et al.
Pubblicazione: (2026)

Hybrid Time-Domain Behavior Model Based on Neural Differential Equations and RNNs
di: Chang, Zenghui, et al.
Pubblicazione: (2025)

Grammar-based Ordinary Differential Equation Discovery
di: Yu, Karin L., et al.
Pubblicazione: (2025)

Low-Dimension-to-High-Dimension Generalization And Its Implications for Length Generalization
di: Chen, Yang, et al.
Pubblicazione: (2024)

Partial Feedback Online Learning
di: Shao, Shihao, et al.
Pubblicazione: (2026)

DrSR: LLM based Scientific Equation Discovery with Dual Reasoning from Data and Experience
di: Wang, Runxiang, et al.
Pubblicazione: (2025)

Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective
di: Chen, Yang, et al.
Pubblicazione: (2024)

Analyzing and Improving Diffusion Models for Time-Series Data Imputation: A Proximal Recursion Perspective
di: Chen, Zhichao, et al.
Pubblicazione: (2026)

Differentiable Constraint-Based Causal Discovery
di: Zhou, Jincheng, et al.
Pubblicazione: (2025)

Does Differentially Private Synthetic Data Lead to Synthetic Discoveries?
di: Perez, Ileana Montoya, et al.
Pubblicazione: (2024)

Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching
di: Jiang, Nan, et al.
Pubblicazione: (2024)

Towards Identifiability of Interventional Stochastic Differential Equations
di: Zweig, Aaron, et al.
Pubblicazione: (2025)

Physics-Informed Neural Networks for Control of Single-Phase Flow Systems Governed by Partial Differential Equations
di: Miyatake, Luis Kin, et al.
Pubblicazione: (2025)

EDC: Equation Discovery for Classification
di: Toussaint, Guus, et al.
Pubblicazione: (2025)

Multi-Task Equation Discovery
di: Bee, S C, et al.
Pubblicazione: (2025)