Saved in:
| Main Authors: | Zhang, Jiahao, Zhang, Shiheng, Lin, Guang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.16395 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Weak-Form Evolutionary Kolmogorov-Arnold Networks for Solving Partial Differential Equations
by: Kim, Bongseok, et al.
Published: (2026)
by: Kim, Bongseok, et al.
Published: (2026)
TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs
by: Dai, Chen-Yang, et al.
Published: (2026)
by: Dai, Chen-Yang, et al.
Published: (2026)
Muon with Spectral Guidance: Efficient Optimization for Scientific Machine Learning
by: Lu, Binghang, et al.
Published: (2026)
by: Lu, Binghang, et al.
Published: (2026)
Mixture-of-Subspaces in Low-Rank Adaptation
by: Wu, Taiqiang, et al.
Published: (2024)
by: Wu, Taiqiang, et al.
Published: (2024)
Autoregression-Free Neural Operators for Time-Dependent PDEs
by: Zhang, Jiaquan, et al.
Published: (2026)
by: Zhang, Jiaquan, et al.
Published: (2026)
Theoretical Guarantees for Low-Rank Compression of Deep Neural Networks
by: Zhang, Shihao, et al.
Published: (2025)
by: Zhang, Shihao, et al.
Published: (2025)
Planner-Admissible Graph-PDE Value Extensions for Sparse Goal-Conditioned Planning
by: Zhang, Shiheng
Published: (2026)
by: Zhang, Shiheng
Published: (2026)
Reduced-Basis Deep Operator Learning for Parametric PDEs with Independently Varying Boundary and Source Data
by: Wang, Yueqi, et al.
Published: (2025)
by: Wang, Yueqi, et al.
Published: (2025)
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
by: Jang, Kyoungseok, et al.
Published: (2024)
by: Jang, Kyoungseok, et al.
Published: (2024)
Low-Rank Adaptation of Neural Fields
by: Truong, Anh, et al.
Published: (2025)
by: Truong, Anh, et al.
Published: (2025)
DeepONet Augmented by Randomized Neural Networks for Efficient Operator Learning in PDEs
by: Jiang, Zhaoxi, et al.
Published: (2025)
by: Jiang, Zhaoxi, et al.
Published: (2025)
Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs
by: Cheng, Chun-Wun, et al.
Published: (2024)
by: Cheng, Chun-Wun, et al.
Published: (2024)
Low Rank Adaptation for Adversarial Perturbation
by: Liu, Han, et al.
Published: (2026)
by: Liu, Han, et al.
Published: (2026)
ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
by: Zhang, Yilang, et al.
Published: (2025)
by: Zhang, Yilang, et al.
Published: (2025)
Spectral Imbalance Causes Forgetting in Low-Rank Continual Adaptation
by: Gu, Hao, et al.
Published: (2026)
by: Gu, Hao, et al.
Published: (2026)
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning
by: Zhang, Boning, et al.
Published: (2024)
by: Zhang, Boning, et al.
Published: (2024)
Latent Neural Operator Pretraining for Solving Time-Dependent PDEs
by: Wang, Tian, et al.
Published: (2024)
by: Wang, Tian, et al.
Published: (2024)
Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions
by: Zhang, Wenhao, et al.
Published: (2026)
by: Zhang, Wenhao, et al.
Published: (2026)
Morephy-Net: An Evolutionary Multi-objective Optimization for Replica-Exchange-based Physics-informed Neural Operator Learning Networks
by: Lu, Binghang, et al.
Published: (2025)
by: Lu, Binghang, et al.
Published: (2025)
The Primacy of Magnitude in Low-Rank Adaptation
by: Zhang, Zicheng, et al.
Published: (2025)
by: Zhang, Zicheng, et al.
Published: (2025)
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
by: Yaras, Can, et al.
Published: (2024)
by: Yaras, Can, et al.
Published: (2024)
DropLoRA: Sparse Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
by: Zhang, Haojie
Published: (2025)
by: Zhang, Haojie
Published: (2025)
Time-Efficient Evaluation and Enhancement of Adversarial Robustness in Deep Neural Networks
by: Lin, Runqi
Published: (2025)
by: Lin, Runqi
Published: (2025)
An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method
by: Zhang, Jiahao, et al.
Published: (2024)
by: Zhang, Jiahao, et al.
Published: (2024)
Dynamic Low-Rank Sparse Adaptation for Large Language Models
by: Huang, Weizhong, et al.
Published: (2025)
by: Huang, Weizhong, et al.
Published: (2025)
Provable Meta-Learning with Low-Rank Adaptations
by: Block, Jacob L., et al.
Published: (2024)
by: Block, Jacob L., et al.
Published: (2024)
Parameter Efficient Continual Learning with Dynamic Low-Rank Adaptation
by: Bhat, Prashant Shivaram, et al.
Published: (2025)
by: Bhat, Prashant Shivaram, et al.
Published: (2025)
RefLoRA: Refactored Low-Rank Adaptation for Efficient Fine-Tuning of Large Models
by: Zhang, Yilang, et al.
Published: (2025)
by: Zhang, Yilang, et al.
Published: (2025)
Physics-Informed Neural Networks and Neural Operators for Parametric PDEs
by: Zhang, Zhuo, et al.
Published: (2025)
by: Zhang, Zhuo, et al.
Published: (2025)
Channel-Aware Low-Rank Adaptation in Time Series Forecasting
by: Nie, Tong, et al.
Published: (2024)
by: Nie, Tong, et al.
Published: (2024)
Low-Rank Adaptation Redux for Large Models
by: Li, Bingcong, et al.
Published: (2026)
by: Li, Bingcong, et al.
Published: (2026)
NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models
by: Lin, Cheng, et al.
Published: (2024)
by: Lin, Cheng, et al.
Published: (2024)
MODE: Efficient Time Series Prediction with Mamba Enhanced by Low-Rank Neural ODEs
by: Chen, Xingsheng, et al.
Published: (2026)
by: Chen, Xingsheng, et al.
Published: (2026)
BEKAN: Boundary condition-guaranteed evolutionary Kolmogorov-Arnold networks with radial basis functions for solving PDE problems
by: Kim, Bongseok, et al.
Published: (2025)
by: Kim, Bongseok, et al.
Published: (2025)
MoR: Mixture of Ranks for Low-Rank Adaptation Tuning
by: Tang, Chuanyu, et al.
Published: (2024)
by: Tang, Chuanyu, et al.
Published: (2024)
Transfer Learning in Physics-Informed Neural Networks: Full Fine-Tuning, Lightweight Fine-Tuning, and Low-Rank Adaptation
by: Wang, Yizheng, et al.
Published: (2025)
by: Wang, Yizheng, et al.
Published: (2025)
Frequency Regularization: Unveiling the Spectral Inductive Bias of Deep Neural Networks
by: Lu, Jiahao
Published: (2025)
by: Lu, Jiahao
Published: (2025)
Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptations
by: Germán-Morales, M., et al.
Published: (2024)
by: Germán-Morales, M., et al.
Published: (2024)
Selective Aggregation for Low-Rank Adaptation in Federated Learning
by: Guo, Pengxin, et al.
Published: (2024)
by: Guo, Pengxin, et al.
Published: (2024)
CLoRA: Parameter-Efficient Continual Learning with Low-Rank Adaptation
by: Muralidhara, Shishir, et al.
Published: (2025)
by: Muralidhara, Shishir, et al.
Published: (2025)
Similar Items
-
Weak-Form Evolutionary Kolmogorov-Arnold Networks for Solving Partial Differential Equations
by: Kim, Bongseok, et al.
Published: (2026) -
TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs
by: Dai, Chen-Yang, et al.
Published: (2026) -
Muon with Spectral Guidance: Efficient Optimization for Scientific Machine Learning
by: Lu, Binghang, et al.
Published: (2026) -
Mixture-of-Subspaces in Low-Rank Adaptation
by: Wu, Taiqiang, et al.
Published: (2024) -
Autoregression-Free Neural Operators for Time-Dependent PDEs
by: Zhang, Jiaquan, et al.
Published: (2026)