Copertina

An Interpretable Evaluation of Entropy-based Novelty of Generative Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Jingwei, Li, Cheuk Ting, Farnia, Farzan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach
di: Zhang, Jingwei, et al.
Pubblicazione: (2024)

Sparse Domain Transfer via Elastic Net Regularization
di: Zhang, Jingwei, et al.
Pubblicazione: (2024)

Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability
di: Ye, Zhuorui, et al.
Pubblicazione: (2024)

SPARKE: Scalable Prompt-Aware Diversity and Novelty Guidance in Diffusion Models via RKE Score
di: Jalali, Mohammad, et al.
Pubblicazione: (2025)

Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations
di: Oskouie, Haniyeh Ehsani, et al.
Pubblicazione: (2022)

PromptSplit: Revealing Prompt-Level Disagreement in Generative Models
di: Lotfian, Mehdi, et al.
Pubblicazione: (2026)

A Super-pixel-based Approach to the Stable Interpretation of Neural Networks
di: Gong, Shizhan, et al.
Pubblicazione: (2024)

When Exploration Comes for Free with Mixture-Greedy: Do we need UCB in Diversity-Aware Multi-Armed Bandits?
di: Nia, Bahar Dibaei, et al.
Pubblicazione: (2026)

Exposing Diversity Bias in Deep Generative Models: Statistical Origins and Correction of Diversity Error
di: Farnia, Farzan, et al.
Pubblicazione: (2026)

Conditional Vendi Score: An Information-Theoretic Approach to Diversity Evaluation of Prompt-based Generative Models
di: Jalali, Mohammad, et al.
Pubblicazione: (2024)

Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training
di: Gong, Shizhan, et al.
Pubblicazione: (2024)

Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
di: Sani, Matina Mahdizadeh, et al.
Pubblicazione: (2026)

DiffPattern-Flex: Efficient Layout Pattern Generation via Discrete Diffusion
di: Wang, Zixiao, et al.
Pubblicazione: (2025)

Towards an Explainable Comparison and Alignment of Feature Embeddings
di: Jalali, Mohammad, et al.
Pubblicazione: (2025)

Scendi Score: Prompt-Aware Diversity Evaluation via Schur Complement of CLIP Embeddings
di: Ospanov, Azim, et al.
Pubblicazione: (2024)

Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models
di: Gong, Shizhan, et al.
Pubblicazione: (2025)

Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms
di: Rezaei, Parham, et al.
Pubblicazione: (2024)

Vendi Novelty Scores for Out-of-Distribution Detection
di: Pasarkar, Amey P., et al.
Pubblicazione: (2026)

SVGen: Interpretable Vector Graphics Generation with Large Language Models
di: Wang, Feiyu, et al.
Pubblicazione: (2025)

Robust Novelty Detection through Style-Conscious Feature Ranking
di: Smeu, Stefan, et al.
Pubblicazione: (2023)

Entropy-Informed Weighting Channel Normalizing Flow for Deep Generative Models
di: Chen, Wei, et al.
Pubblicazione: (2024)

DRIMV_TSK: An Interpretable Surgical Evaluation Model for Incomplete Multi-View Rectal Cancer Data
di: Zhang, Wei, et al.
Pubblicazione: (2025)

Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability
di: Hwang, Jaehui, et al.
Pubblicazione: (2023)

A Lightweight Generative Model for Interpretable Subject-level Prediction
di: Mauri, Chiara, et al.
Pubblicazione: (2023)

Concept-Centric Token Interpretation for Vector-Quantized Generative Models
di: Yang, Tianze, et al.
Pubblicazione: (2025)

Interpretable Generative Models through Post-hoc Concept Bottlenecks
di: Kulkarni, Akshay, et al.
Pubblicazione: (2025)

Deep Model Interpretation with Limited Data : A Coreset-based Approach
di: Behzadi-Khormouji, Hamed, et al.
Pubblicazione: (2024)

Beyond the Known: Adversarial Autoencoders in Novelty Detection
di: Asad, Muhammad, et al.
Pubblicazione: (2024)

Moderating the Generalization of Score-based Generative Model
di: Jiang, Wan, et al.
Pubblicazione: (2024)

BEM: Balanced and Entropy-based Mix for Long-Tailed Semi-Supervised Learning
di: Zheng, Hongwei, et al.
Pubblicazione: (2024)

Domain-Enhanced Dual-Branch Model for Efficient and Interpretable Accident Anticipation
di: Guan, Yanchen, et al.
Pubblicazione: (2025)

LookingGlass: Generative Anamorphoses via Laplacian Pyramid Warping
di: Chang, Pascal, et al.
Pubblicazione: (2025)

Riemannian Motion Generation: A Unified Framework for Human Motion Representation and Generation via Riemannian Flow Matching
di: Miao, Fangran, et al.
Pubblicazione: (2026)

MER-DG: Modality-Entropy Regularization for Multimodal Domain Generalization
di: Yarici, Yavuz, et al.
Pubblicazione: (2026)

How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
di: Chang, Pascal, et al.
Pubblicazione: (2025)

CASL: Concept-Aligned Sparse Latents for Interpreting Diffusion Models
di: He, Zhenghao, et al.
Pubblicazione: (2026)

GMValuator: Similarity-based Data Valuation for Generative Models
di: Yang, Jiaxi, et al.
Pubblicazione: (2023)

CIP-Net: Continual Interpretable Prototype-based Network
di: Di Valerio, Federico, et al.
Pubblicazione: (2025)

Beyond Top Activations: Efficient and Reliable Crowdsourced Evaluation of Automated Interpretability
di: Oikarinen, Tuomas, et al.
Pubblicazione: (2025)

Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples
di: Jiralerspong, Marco, et al.
Pubblicazione: (2023)