Complex Equation Learner: Rational Symbolic Regression with Gradient Descent in Complex Domain
Fuente:
arXiv
Saved in:
| Main Authors: | Garmaev, Sergei, Gauché, Maurice, Fink, Olga |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
NOMTO: Neural Operator-based symbolic Model approximaTion and discOvery
by: Garmaev, Sergei, et al.
Published: (2025)
by: Garmaev, Sergei, et al.
Published: (2025)
Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients
by: Bastiani, Zachary, et al.
Published: (2024)
by: Bastiani, Zachary, et al.
Published: (2024)
Neural Symbolic Regression of Complex Network Dynamics
by: Qiu, Haiquan, et al.
Published: (2024)
by: Qiu, Haiquan, et al.
Published: (2024)
Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion
by: Niresi, Keivan Faghih, et al.
Published: (2024)
by: Niresi, Keivan Faghih, et al.
Published: (2024)
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)
by: Livni, Roi
Published: (2024)
Stochastic Gradient Descent for Nonparametric Additive Regression
by: Chen, Xin, et al.
Published: (2024)
by: Chen, Xin, et al.
Published: (2024)
Uncertainty-Guided Alignment for Unsupervised Domain Adaptation in Regression
by: Nejjar, Ismail, et al.
Published: (2024)
by: Nejjar, Ismail, et al.
Published: (2024)
Learning Curves of Stochastic Gradient Descent in Kernel Regression
by: Zhang, Haihan, et al.
Published: (2025)
by: Zhang, Haihan, et al.
Published: (2025)
Interactive Symbolic Regression through Offline Reinforcement Learning: A Co-Design Framework
by: Tian, Yuan, et al.
Published: (2024)
by: Tian, Yuan, et al.
Published: (2024)
Beyond Accuracy and Complexity: The Effective Information Criterion for Structurally Stable Symbolic Regression
by: Yu, Zihan, et al.
Published: (2025)
by: Yu, Zihan, et al.
Published: (2025)
IM-Context: In-Context Learning for Imbalanced Regression Tasks
by: Nejjar, Ismail, et al.
Published: (2024)
by: Nejjar, Ismail, et al.
Published: (2024)
Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression
by: Wu, Jingfeng, et al.
Published: (2025)
by: Wu, Jingfeng, et al.
Published: (2025)
Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression
by: Wu, Jingfeng, et al.
Published: (2025)
by: Wu, Jingfeng, et al.
Published: (2025)
Domain Adaptive Unfolded Graph Neural Networks
by: Zhang, Zepeng, et al.
Published: (2024)
by: Zhang, Zepeng, et al.
Published: (2024)
Interactive Symbolic Regression through Offline Reinforcement Learning: A Co-Design Framework
by: Tian, Yuan, et al.
Published: (2025)
by: Tian, Yuan, et al.
Published: (2025)
Data-Informed Model Complexity Metric for Optimizing Symbolic Regression Models
by: Haut, Nathan, et al.
Published: (2025)
by: Haut, Nathan, et al.
Published: (2025)
Alleviating Overfitting in Transformation-Interaction-Rational Symbolic Regression with Multi-Objective Optimization
by: de Franca, Fabricio Olivetti
Published: (2025)
by: de Franca, Fabricio Olivetti
Published: (2025)
Trained Mamba Emulates Online Gradient Descent in In-Context Linear Regression
by: Jiang, Jiarui, et al.
Published: (2025)
by: Jiang, Jiarui, et al.
Published: (2025)
Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression
by: Ding, Shihong, et al.
Published: (2025)
by: Ding, Shihong, et al.
Published: (2025)
Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression
by: Kale, Sacchit, et al.
Published: (2026)
by: Kale, Sacchit, et al.
Published: (2026)
Controlled Generation of Unseen Faults for Partial and Open-Partial Domain Adaptation
by: Rombach, Katharina, et al.
Published: (2022)
by: Rombach, Katharina, et al.
Published: (2022)
Tight Bounds for Logistic Regression with Large Stepsize Gradient Descent in Low Dimension
by: Crawshaw, Michael, et al.
Published: (2026)
by: Crawshaw, Michael, et al.
Published: (2026)
Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent
by: Zhang, Chenyang, et al.
Published: (2026)
by: Zhang, Chenyang, et al.
Published: (2026)
Vertical Symbolic Regression via Deep Policy Gradient
by: Jiang, Nan, et al.
Published: (2024)
by: Jiang, Nan, et al.
Published: (2024)
Scaled Gradient Descent for Ill-Conditioned Low-Rank Matrix Recovery with Optimal Sampling Complexity
by: Li, Zhenxuan, et al.
Published: (2026)
by: Li, Zhenxuan, et al.
Published: (2026)
Full-Batch Gradient Descent Outperforms One-Pass SGD: Sample Complexity Separation in Single-Index Learning
by: Kovačević, Filip, et al.
Published: (2026)
by: Kovačević, Filip, et al.
Published: (2026)
GENSR: Symbolic Regression Based in Equation Generative Space
by: Li, Qian, et al.
Published: (2026)
by: Li, Qian, et al.
Published: (2026)
Iteration and Stochastic First-order Oracle Complexities of Stochastic Gradient Descent using Constant and Decaying Learning Rates
by: Imaizumi, Kento, et al.
Published: (2024)
by: Imaizumi, Kento, et al.
Published: (2024)
Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors
by: Huang, Sikai, et al.
Published: (2025)
by: Huang, Sikai, et al.
Published: (2025)
Stochastic Differential Equations models for Least-Squares Stochastic Gradient Descent
by: Schertzer, Adrien, et al.
Published: (2024)
by: Schertzer, Adrien, et al.
Published: (2024)
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes
by: Zhang, Ruiqi, et al.
Published: (2025)
by: Zhang, Ruiqi, et al.
Published: (2025)
From Logistic Regression to the Perceptron Algorithm: Exploring Gradient Descent with Large Step Sizes
by: Tyurin, Alexander
Published: (2024)
by: Tyurin, Alexander
Published: (2024)
When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate
by: Forest, Florent, et al.
Published: (2025)
by: Forest, Florent, et al.
Published: (2025)
Occam Gradient Descent
by: Kausik, B. N.
Published: (2024)
by: Kausik, B. N.
Published: (2024)
Domain Generalization by Functional Regression
by: Holzleitner, Markus, et al.
Published: (2023)
by: Holzleitner, Markus, et al.
Published: (2023)
Gradient Descent is Pareto-Optimal in the Oracle Complexity and Memory Tradeoff for Feasibility Problems
by: Blanchard, Moise
Published: (2024)
by: Blanchard, Moise
Published: (2024)
Gradient Descent on Logistic Regression with Non-Separable Data and Large Step Sizes
by: Meng, Si Yi, et al.
Published: (2024)
by: Meng, Si Yi, et al.
Published: (2024)
Graph Neural Networks for Virtual Sensing in Complex Systems: Addressing Heterogeneous Temporal Dynamics
by: Zhao, Mengjie, et al.
Published: (2024)
by: Zhao, Mengjie, et al.
Published: (2024)
Heterogeneous Graph Neural Networks for Short-term State Forecasting in Power Systems across Domains and Time Scales: A Hydroelectric Power Plant Case Study
by: Theiler, Raffael, et al.
Published: (2025)
by: Theiler, Raffael, et al.
Published: (2025)
Prior-Guided Symbolic Regression: Towards Scientific Consistency in Equation Discovery
by: Xiao, Jing, et al.
Published: (2026)
by: Xiao, Jing, et al.
Published: (2026)
Similar Items
-
NOMTO: Neural Operator-based symbolic Model approximaTion and discOvery
by: Garmaev, Sergei, et al.
Published: (2025) -
Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients
by: Bastiani, Zachary, et al.
Published: (2024) -
Neural Symbolic Regression of Complex Network Dynamics
by: Qiu, Haiquan, et al.
Published: (2024) -
Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion
by: Niresi, Keivan Faghih, et al.
Published: (2024) -
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)