Guardado en:
| Autores principales: | Wang, Yuanchao, Lai, Zhao-Rong, Zhong, Tianqi |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2502.19665 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Environment-Conditioned Tail Reweighting for Total Variation Invariant Risk Minimization
por: Wang, Yuanchao, et al.
Publicado: (2026)
por: Wang, Yuanchao, et al.
Publicado: (2026)
Invariant Risk Minimization Is A Total Variation Model
por: Lai, Zhao-Rong, et al.
Publicado: (2024)
por: Lai, Zhao-Rong, et al.
Publicado: (2024)
Out-of-Distribution Optimality of Invariant Risk Minimization
por: Toyota, Shoji, et al.
Publicado: (2023)
por: Toyota, Shoji, et al.
Publicado: (2023)
Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
por: Wang, Song, et al.
Publicado: (2025)
por: Wang, Song, et al.
Publicado: (2025)
Tree-based Ensemble Learning for Out-of-distribution Detection
por: Shen, Zhaiming, et al.
Publicado: (2024)
por: Shen, Zhaiming, et al.
Publicado: (2024)
Invariant Graph Transformer for Out-of-Distribution Generalization
por: Liao, Tianyin, et al.
Publicado: (2025)
por: Liao, Tianyin, et al.
Publicado: (2025)
Unsupervised Representation Learning - an Invariant Risk Minimization Perspective
por: Norman, Yotam, et al.
Publicado: (2025)
por: Norman, Yotam, et al.
Publicado: (2025)
Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration
por: Yoshida, Kotaro, et al.
Publicado: (2024)
por: Yoshida, Kotaro, et al.
Publicado: (2024)
Deceptive Risk Minimization: Out-of-Distribution Generalization by Deceiving Distribution Shift Detectors
por: Majumdar, Anirudha
Publicado: (2025)
por: Majumdar, Anirudha
Publicado: (2025)
Out-of-Context Misinformation Detection via Variational Domain-Invariant Learning with Test-Time Training
por: Yang, Xi, et al.
Publicado: (2025)
por: Yang, Xi, et al.
Publicado: (2025)
BootOOD: Self-Supervised Out-of-Distribution Detection via Synthetic Sample Exposure under Neural Collapse
por: Wang, Yuanchao, et al.
Publicado: (2025)
por: Wang, Yuanchao, et al.
Publicado: (2025)
Towards Understanding the Role of Sharpness-Aware Minimization Algorithms for Out-of-Distribution Generalization
por: Schapiro, Samuel, et al.
Publicado: (2024)
por: Schapiro, Samuel, et al.
Publicado: (2024)
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
por: Mao, Wenyu, et al.
Publicado: (2024)
por: Mao, Wenyu, et al.
Publicado: (2024)
A Simpler Alternative to Variational Regularized Counterfactual Risk Minimization
por: Bakker, Hua Chang, et al.
Publicado: (2024)
por: Bakker, Hua Chang, et al.
Publicado: (2024)
Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization
por: Zhang, Simon, et al.
Publicado: (2026)
por: Zhang, Simon, et al.
Publicado: (2026)
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
por: Liu, Haoxin, et al.
Publicado: (2024)
por: Liu, Haoxin, et al.
Publicado: (2024)
Feature Protection For Out-of-distribution Generalization
por: Tan, Lu, et al.
Publicado: (2024)
por: Tan, Lu, et al.
Publicado: (2024)
Improving Graph Out-of-distribution Generalization Beyond Causality
por: Xu, Can, et al.
Publicado: (2024)
por: Xu, Can, et al.
Publicado: (2024)
Data-Driven Generation of Neutron Star Equations of State Using Variational Autoencoders
por: Ross, Alex, et al.
Publicado: (2026)
por: Ross, Alex, et al.
Publicado: (2026)
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection
por: Liao, Xinting, et al.
Publicado: (2024)
por: Liao, Xinting, et al.
Publicado: (2024)
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
por: Liu, Yibing, et al.
Publicado: (2023)
por: Liu, Yibing, et al.
Publicado: (2023)
Can In-context Learning Really Generalize to Out-of-distribution Tasks?
por: Wang, Qixun, et al.
Publicado: (2024)
por: Wang, Qixun, et al.
Publicado: (2024)
Mixture Data for Training Cannot Ensure Out-of-distribution Generalization
por: Zhang, Songming, et al.
Publicado: (2023)
por: Zhang, Songming, et al.
Publicado: (2023)
diffIRM: A Diffusion-Augmented Invariant Risk Minimization Framework for Spatiotemporal Prediction over Graphs
por: Mo, Zhaobin, et al.
Publicado: (2024)
por: Mo, Zhaobin, et al.
Publicado: (2024)
Analysis of Total Variation Minimization for Clustered Federated Learning
por: Jung, A.
Publicado: (2024)
por: Jung, A.
Publicado: (2024)
Topology-aware Robust Optimization for Out-of-distribution Generalization
por: Qiao, Fengchun, et al.
Publicado: (2023)
por: Qiao, Fengchun, et al.
Publicado: (2023)
Spurious Feature Diversification Improves Out-of-distribution Generalization
por: Lin, Yong, et al.
Publicado: (2023)
por: Lin, Yong, et al.
Publicado: (2023)
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
por: Chen, Jinggang, et al.
Publicado: (2023)
por: Chen, Jinggang, et al.
Publicado: (2023)
Universally Invariant Learning in Equivariant GNNs
por: Cen, Jiacheng, et al.
Publicado: (2025)
por: Cen, Jiacheng, et al.
Publicado: (2025)
Linear Trading Position with Sparse Spectrum
por: Lai, Zhao-Rong, et al.
Publicado: (2025)
por: Lai, Zhao-Rong, et al.
Publicado: (2025)
Variational f-divergence Minimization
por: Zhang, Mingtian, et al.
Publicado: (2019)
por: Zhang, Mingtian, et al.
Publicado: (2019)
BOOD: Boundary-based Out-Of-Distribution Data Generation
por: Liao, Qilin, et al.
Publicado: (2025)
por: Liao, Qilin, et al.
Publicado: (2025)
Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problems
por: Li, Bingcong, et al.
Publicado: (2024)
por: Li, Bingcong, et al.
Publicado: (2024)
Functional Risk Minimization
por: Alet, Ferran, et al.
Publicado: (2024)
por: Alet, Ferran, et al.
Publicado: (2024)
GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification
por: Zhao, Tianqi, et al.
Publicado: (2024)
por: Zhao, Tianqi, et al.
Publicado: (2024)
Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
por: Tieu, Katherine, et al.
Publicado: (2025)
por: Tieu, Katherine, et al.
Publicado: (2025)
Mining In-distribution Attributes in Outliers for Out-of-distribution Detection
por: Lei, Yutian, et al.
Publicado: (2024)
por: Lei, Yutian, et al.
Publicado: (2024)
KAN based Autoencoders for Factor Models
por: Wang, Tianqi, et al.
Publicado: (2024)
por: Wang, Tianqi, et al.
Publicado: (2024)
Discriminative Estimation of Total Variation Distance: A Fidelity Auditor for Generative Data
por: Tao, Lan, et al.
Publicado: (2024)
por: Tao, Lan, et al.
Publicado: (2024)
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
por: Yang, Shenzhi, et al.
Publicado: (2025)
por: Yang, Shenzhi, et al.
Publicado: (2025)
Ejemplares similares
-
Environment-Conditioned Tail Reweighting for Total Variation Invariant Risk Minimization
por: Wang, Yuanchao, et al.
Publicado: (2026) -
Invariant Risk Minimization Is A Total Variation Model
por: Lai, Zhao-Rong, et al.
Publicado: (2024) -
Out-of-Distribution Optimality of Invariant Risk Minimization
por: Toyota, Shoji, et al.
Publicado: (2023) -
Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
por: Wang, Song, et al.
Publicado: (2025) -
Tree-based Ensemble Learning for Out-of-distribution Detection
por: Shen, Zhaiming, et al.
Publicado: (2024)