Copertina

Non-Parametric Probabilistic Robustness: A Conservative Risk Estimator under Unknown Perturbation Distributions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Zheng, Zhang, Yi, Khastgir, Siddartha, Maple, Carsten, Zhao, Xingyu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computer Vision and Pattern Recognition Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

PRBench: A Standardized Probabilistic Robustness Benchmark
di: Zhang, Yi, et al.
Pubblicazione: (2025)

ProTIP: Probabilistic Robustness Verification on Text-to-Image Diffusion Models against Stochastic Perturbation
di: Zhang, Yi, et al.
Pubblicazione: (2024)

Probabilistic Segmentation for Robust Field of View Estimation
di: Hallyburton, R. Spencer, et al.
Pubblicazione: (2025)

Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks
di: Zhang, Lei, et al.
Pubblicazione: (2024)

SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise
di: Feng, Chen, et al.
Pubblicazione: (2021)

Class-Conditional Distribution Balancing for Group Robust Classification
di: Zhao, Miaoyun, et al.
Pubblicazione: (2025)

Verifying Robust Unlearning: Probing Residual Knowledge in Unlearned Models
di: Xuan, Hao, et al.
Pubblicazione: (2025)

Physically-Induced Atmospheric Adversarial Perturbations: Enhancing Transferability and Robustness in Remote Sensing Image Classification
di: Zhuang, Weiwei, et al.
Pubblicazione: (2026)

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning
di: Silva, Thalles, et al.
Pubblicazione: (2025)

Data-Agnostic Augmentations for Unknown Variations: Out-of-Distribution Generalisation in MRI Segmentation
di: Vaish, Puru, et al.
Pubblicazione: (2025)

Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations
di: Hu, Hanjiang, et al.
Pubblicazione: (2023)

Robust Monocular Depth Estimation under Challenging Conditions
di: Gasperini, Stefano, et al.
Pubblicazione: (2023)

AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks
di: Li, Jin, et al.
Pubblicazione: (2025)

Uncertainty-Aware Subset Selection for Robust Visual Explainability under Distribution Shifts
di: Gupta, Madhav, et al.
Pubblicazione: (2025)

Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge
di: Wang, Jingge, et al.
Pubblicazione: (2022)

Feature Space Perturbation: A Panacea to Enhanced Transferability Estimation
di: Khoba, Prafful Kumar, et al.
Pubblicazione: (2025)

Boosting the Robustness-Accuracy Trade-off of SNNs by Robust Temporal Self-Ensemble
di: Wang, Jihang, et al.
Pubblicazione: (2025)

Scalable Class-Incremental Learning Based on Parametric Neural Collapse
di: Zhang, Chuangxin, et al.
Pubblicazione: (2025)

Assessing Uncertainty Estimation Methods for 3D Image Segmentation under Distribution Shifts
di: Javanbakhat, Masoumeh, et al.
Pubblicazione: (2024)

Hierarchical Multi-Graphs Learning for Robust Group Re-Identification
di: Liu, Ruiqi, et al.
Pubblicazione: (2024)

Parametric $ρ$-Norm Scaling Calibration
di: Zhang, Siyuan, et al.
Pubblicazione: (2024)

Symmetry-Robust 3D Orientation Estimation
di: Scarvelis, Christopher, et al.
Pubblicazione: (2024)

SELU: Self-Learning Embodied MLLMs in Unknown Environments
di: Li, Boyu, et al.
Pubblicazione: (2024)

Group Distributionally Robust Dataset Distillation with Risk Minimization
di: Vahidian, Saeed, et al.
Pubblicazione: (2024)

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation
di: Lee, Junha, et al.
Pubblicazione: (2024)

OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
di: Li, Lin, et al.
Pubblicazione: (2023)

Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features
di: Silva, Thalles, et al.
Pubblicazione: (2024)

REDistill: Robust Estimator Distillation for Balancing Robustness and Efficiency
di: Tybl, Ondrej, et al.
Pubblicazione: (2026)

PaRCE: Probabilistic and Reconstruction-based Competency Estimation for CNN-based Image Classification
di: Pohland, Sara, et al.
Pubblicazione: (2024)

Towards Robust Universal Perturbation Attacks: A Float-Coded, Penalty-Driven Evolutionary Approach
di: Wang, Shiqi, et al.
Pubblicazione: (2026)

ProHOC: Probabilistic Hierarchical Out-of-Distribution Classification via Multi-Depth Networks
di: Wallin, Erik, et al.
Pubblicazione: (2025)

Beyond a Single Signal: SPECTREG2, A Unified MultiExpert Anomaly Detector for Unknown Unknowns
di: Ray, Rahul D
Pubblicazione: (2026)

Towards Fair Class-wise Robustness: Class Optimal Distribution Adversarial Training
di: Zhi, Hongxin, et al.
Pubblicazione: (2025)

NPNet: A Non-Parametric Network with Adaptive Gaussian-Fourier Positional Encoding for 3D Classification and Segmentation
di: Saeid, Mohammad, et al.
Pubblicazione: (2026)

CPA-Enhancer: Chain-of-Thought Prompted Adaptive Enhancer for Object Detection under Unknown Degradations
di: Zhang, Yuwei, et al.
Pubblicazione: (2024)

Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World
di: Lei, Bowen, et al.
Pubblicazione: (2024)

Knowing the Unknown: Interpretable Open-World Object Detection via Concept Decomposition Model
di: Lv, Xueqiang, et al.
Pubblicazione: (2026)

DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection
di: Geng, Jingyao, et al.
Pubblicazione: (2024)

ProSub: Probabilistic Open-Set Semi-Supervised Learning with Subspace-Based Out-of-Distribution Detection
di: Wallin, Erik, et al.
Pubblicazione: (2024)

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models
di: Zeng, Qian, et al.
Pubblicazione: (2025)