Interpretable Operator Learning for Inverse Problems via Adaptive Spectral Filtering: Convergence and Discretization Invariance
Fuente:
arXiv
Saved in:
| Main Authors: | Dong, Hang-Cheng, Cheng, Pengcheng, Li, Shuhuan |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quotient Geometry, Effective Curvature, and Implicit Bias in Simple Shallow Neural Networks
by: Dong, Hang-Cheng, et al.
Published: (2026)
by: Dong, Hang-Cheng, et al.
Published: (2026)
Gauge-Equivariant Intrinsic Neural Operators for Geometry-Consistent Learning of Elliptic PDE Maps
by: Cheng, Pengcheng
Published: (2026)
by: Cheng, Pengcheng
Published: (2026)
SFO: Learning PDE Operators via Spectral Filtering
by: Koren, Noam, et al.
Published: (2026)
by: Koren, Noam, et al.
Published: (2026)
Operator-Guided Invariance Learning for Continuous Reinforcement Learning
by: Zhang, Zuyuan, et al.
Published: (2026)
by: Zhang, Zuyuan, et al.
Published: (2026)
Spectral Clustering for Discrete Distributions
by: Wang, Zixiao, et al.
Published: (2024)
by: Wang, Zixiao, et al.
Published: (2024)
Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems
by: Zhang, Jiawei, et al.
Published: (2024)
by: Zhang, Jiawei, et al.
Published: (2024)
STNet: Spectral Transformation Network for Solving Operator Eigenvalue Problem
by: Wang, Hong, et al.
Published: (2025)
by: Wang, Hong, et al.
Published: (2025)
Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering
by: Guo, Jingwei, et al.
Published: (2024)
by: Guo, Jingwei, et al.
Published: (2024)
Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning
by: Xie, Sean, et al.
Published: (2022)
by: Xie, Sean, et al.
Published: (2022)
Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
by: Kim, Dohyeong, et al.
Published: (2024)
by: Kim, Dohyeong, et al.
Published: (2024)
Continuous Invariance Learning
by: Lin, Yong, et al.
Published: (2023)
by: Lin, Yong, et al.
Published: (2023)
InverseScope: Scalable Activation Inversion for Interpreting Large Language Models
by: Luo, Yifan, et al.
Published: (2025)
by: Luo, Yifan, et al.
Published: (2025)
On the Convergence of Continual Learning with Adaptive Methods
by: Han, Seungyub, et al.
Published: (2024)
by: Han, Seungyub, et al.
Published: (2024)
StaTS: Spectral Trajectory Schedule Learning for Adaptive Time Series Forecasting with Frequency Guided Denoiser
by: Zhang, Jintao, et al.
Published: (2026)
by: Zhang, Jintao, et al.
Published: (2026)
HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations
by: Zhang, Shuaicheng, et al.
Published: (2025)
by: Zhang, Shuaicheng, et al.
Published: (2025)
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
by: Dong, Yushun, et al.
Published: (2024)
by: Dong, Yushun, et al.
Published: (2024)
Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem
by: Huang, Chen, et al.
Published: (2024)
by: Huang, Chen, et al.
Published: (2024)
Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship
by: Nguyen, Nang Hung, et al.
Published: (2026)
by: Nguyen, Nang Hung, et al.
Published: (2026)
TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion
by: Wu, Zhikai, et al.
Published: (2025)
by: Wu, Zhikai, et al.
Published: (2025)
DPCformer: An Interpretable Deep Learning Model for Genomic Prediction in Crops
by: Deng, Pengcheng, et al.
Published: (2025)
by: Deng, Pengcheng, et al.
Published: (2025)
Learning with Exact Invariances in Polynomial Time
by: Soleymani, Ashkan, et al.
Published: (2025)
by: Soleymani, Ashkan, et al.
Published: (2025)
SILO: Solving Inverse Problems with Latent Operators
by: Raphaeli, Ron, et al.
Published: (2025)
by: Raphaeli, Ron, et al.
Published: (2025)
Graph VQ-Transformer (GVT): Fast and Accurate Molecular Generation via High-Fidelity Discrete Latents
by: Zheng, Haozhuo, et al.
Published: (2025)
by: Zheng, Haozhuo, et al.
Published: (2025)
ASPECT: Node-Level Adaptive Spectral Fusion for Graph Contrastive Learning
by: Li, Zhuolong, et al.
Published: (2026)
by: Li, Zhuolong, et al.
Published: (2026)
Filter then Attend: Improving attention-based Time Series Forecasting with Spectral Filtering
by: Dayag, Elisha, et al.
Published: (2025)
by: Dayag, Elisha, et al.
Published: (2025)
Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)
by: Shi, Zhihao, et al.
Published: (2025)
Spectral-inspired Operator Learning with Limited Data and Unknown Physics
by: Wan, Han, et al.
Published: (2025)
by: Wan, Han, et al.
Published: (2025)
Is Optimal Transport Necessary for Inverse Reinforcement Learning?
by: Dong, Zixuan, et al.
Published: (2025)
by: Dong, Zixuan, et al.
Published: (2025)
Learning Action-based Representations Using Invariance
by: Rudolph, Max, et al.
Published: (2024)
by: Rudolph, Max, et al.
Published: (2024)
IR$^3$: Contrastive Inverse Reinforcement Learning for Interpretable Detection and Mitigation of Reward Hacking
by: Beigi, Mohammad, et al.
Published: (2026)
by: Beigi, Mohammad, et al.
Published: (2026)
Offline Reinforcement Learning with Discrete Diffusion Skills
by: Qiao, RuiXi, et al.
Published: (2025)
by: Qiao, RuiXi, et al.
Published: (2025)
Operator Learning with Domain Decomposition for Geometry Generalization in PDE Solving
by: Huang, Jianing, et al.
Published: (2025)
by: Huang, Jianing, et al.
Published: (2025)
From Eigenmodes to Proofs: Integrating Graph Spectral Operators with Symbolic Interpretable Reasoning
by: Kiruluta, Andrew, et al.
Published: (2025)
by: Kiruluta, Andrew, et al.
Published: (2025)
Spectral Flattening Is All Muon Needs: How Orthogonalization Controls Learning Rate and Convergence
by: Nguyen, Tien-Phat, et al.
Published: (2026)
by: Nguyen, Tien-Phat, et al.
Published: (2026)
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
by: Wu, Tailin, et al.
Published: (2024)
by: Wu, Tailin, et al.
Published: (2024)
Interpretable Classification via a Rule Network with Selective Logical Operators
by: Wei, Bowen, et al.
Published: (2024)
by: Wei, Bowen, et al.
Published: (2024)
HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)
by: Feng, Shibo, et al.
Published: (2025)
Provable Length Generalization in Sequence Prediction via Spectral Filtering
by: Marsden, Annie, et al.
Published: (2024)
by: Marsden, Annie, et al.
Published: (2024)
Bayesian Inverse Problems Meet Flow Matching: Efficient and Flexible Inference via Transformers
by: Sherki, Daniil, et al.
Published: (2025)
by: Sherki, Daniil, et al.
Published: (2025)
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
by: Wu, Yuxuan, et al.
Published: (2024)
by: Wu, Yuxuan, et al.
Published: (2024)
Similar Items
-
Quotient Geometry, Effective Curvature, and Implicit Bias in Simple Shallow Neural Networks
by: Dong, Hang-Cheng, et al.
Published: (2026) -
Gauge-Equivariant Intrinsic Neural Operators for Geometry-Consistent Learning of Elliptic PDE Maps
by: Cheng, Pengcheng
Published: (2026) -
SFO: Learning PDE Operators via Spectral Filtering
by: Koren, Noam, et al.
Published: (2026) -
Operator-Guided Invariance Learning for Continuous Reinforcement Learning
by: Zhang, Zuyuan, et al.
Published: (2026) -
Spectral Clustering for Discrete Distributions
by: Wang, Zixiao, et al.
Published: (2024)