Copertina

Explaining Representation by Mutual Information

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Gu, Lifeng
Natura:	Preprint
Pubblicazione:	2021
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

Explicit Mutual Information Maximization for Self-Supervised Learning
di: Chang, Lele, et al.
Pubblicazione: (2024)

Mutual Information calculation on different appearances
di: Liao, Jiecheng, et al.
Pubblicazione: (2024)

RFMI: Estimating Mutual Information on Rectified Flow for Text-to-Image Alignment
di: Wang, Chao, et al.
Pubblicazione: (2025)

MIO : Mutual Information Optimization using Self-Supervised Binary Contrastive Learning
di: Manna, Siladittya, et al.
Pubblicazione: (2021)

Sky Background Building of Multi-objective Fiber spectra Based on Mutual Information Network
di: Zhang, Hui, et al.
Pubblicazione: (2025)

Style Feature Extraction Using Contrastive Conditioned Variational Autoencoders with Mutual Information Constraints
di: Yasutomi, Suguru, et al.
Pubblicazione: (2023)

Explore More, Learn Better: Parallel MLLM Embeddings under Mutual Information Minimization
di: Wang, Zhicheng, et al.
Pubblicazione: (2025)

ORACLE: Leveraging Mutual Information for Consistent Character Generation with LoRAs in Diffusion Models
di: Akdemir, Kiymet, et al.
Pubblicazione: (2024)

ReMem: Mutual Information-Aware Fine-tuning of Pretrained Vision Transformers for Effective Knowledge Distillation
di: Dong, Chengyu, et al.
Pubblicazione: (2025)

MI CAM: Mutual Information Weighted Activation Mapping for Causal Visual Explanations of Convolutional Neural Networks
di: Iyer, Ram S, et al.
Pubblicazione: (2025)

MMRL: Multi-Modal Representation Learning for Vision-Language Models
di: Guo, Yuncheng, et al.
Pubblicazione: (2025)

LatentExplainer: Explaining Latent Representations in Deep Generative Models with Multimodal Large Language Models
di: Zhu, Mengdan, et al.
Pubblicazione: (2024)

DXAI: Explaining Classification by Image Decomposition
di: Kadar, Elnatan, et al.
Pubblicazione: (2023)

Mutually Causal Semantic Distillation Network for Zero-Shot Learning
di: Chen, Shiming, et al.
Pubblicazione: (2026)

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
di: Pham, Cuong, et al.
Pubblicazione: (2024)

ReasonDrive: Efficient Visual Question Answering for Autonomous Vehicles with Reasoning-Enhanced Small Vision-Language Models
di: Chahe, Amirhosein, et al.
Pubblicazione: (2025)

Query3D: LLM-Powered Open-Vocabulary Scene Segmentation with Language Embedded 3D Gaussian
di: Chahe, Amirhosein, et al.
Pubblicazione: (2024)

Inductive Gradient Adjustment For Spectral Bias In Implicit Neural Representations
di: Shi, Kexuan, et al.
Pubblicazione: (2024)

Q-SENN: Quantized Self-Explaining Neural Networks
di: Norrenbrock, Thomas, et al.
Pubblicazione: (2023)

What is Missing? Explaining Neurons Activated by Absent Concepts
di: Hesse, Robin, et al.
Pubblicazione: (2026)

Multimodal Neurodegenerative Disease Subtyping Explained by ChatGPT
di: Reyes, Diego Machado, et al.
Pubblicazione: (2024)

Disentangled Representation Learning with Transmitted Information Bottleneck
di: Dang, Zhuohang, et al.
Pubblicazione: (2023)

Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction Recognition
di: Liu, Mengyuan, et al.
Pubblicazione: (2024)

RegMix: Adversarial Mutual and Generalization Regularization for Enhancing DNN Robustness
di: Liu, Zhenyu, et al.
Pubblicazione: (2025)

PCM-SAR: Physics-Driven Contrastive Mutual Learning for SAR Classification
di: Wang, Pengfei, et al.
Pubblicazione: (2025)

Multi-Cell Decoder and Mutual Learning for Table Structure and Character Recognition
di: Kawakatsu, Takaya
Pubblicazione: (2024)

Mutual Information Analysis in Multimodal Learning Systems
di: Hadizadeh, Hadi, et al.
Pubblicazione: (2024)

Explaining the Impact of Training on Vision Models via Activation Clustering
di: Boubekki, Ahcène, et al.
Pubblicazione: (2024)

Mixup Augmentation with Multiple Interpolations
di: Shen, Lifeng, et al.
Pubblicazione: (2024)

Enhancing Interpretability of Sparse Latent Representations with Class Information
di: Abiz, Farshad Sangari, et al.
Pubblicazione: (2025)

Hidden Monotonicity: Explaining Deep Neural Networks via their DC Decomposition
di: Zimmermann, Jakob Paul, et al.
Pubblicazione: (2026)

Maximizing Information in Domain-Invariant Representation Improves Transfer Learning
di: Li, Adrian Shuai, et al.
Pubblicazione: (2023)

Locally Explaining Prediction Behavior via Gradual Interventions and Measuring Property Gradients
di: Penzel, Niklas, et al.
Pubblicazione: (2025)

PSF-Med: Measuring and Explaining Paraphrase Sensitivity in Medical Vision Language Models
di: Sadanandan, Binesh, et al.
Pubblicazione: (2026)

Learning Decomposable and Debiased Representations via Attribute-Centric Information Bottlenecks
di: Hong, Jinyung, et al.
Pubblicazione: (2024)

Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness
di: Emam, Ahmed, et al.
Pubblicazione: (2023)

TExplain: Explaining Learned Visual Features via Pre-trained (Frozen) Language Models
di: Taghanaki, Saeid Asgari, et al.
Pubblicazione: (2023)

Explaining Vision GNNs: A Semantic and Visual Analysis of Graph-based Image Classification
di: Chaidos, Nikolaos, et al.
Pubblicazione: (2025)

CauSkelNet: Causal Representation Learning for Human Behaviour Analysis
di: Gu, Xingrui, et al.
Pubblicazione: (2024)

Uncovering Semantic Selectivity of Latent Groups in Higher Visual Cortex with Mutual Information-Guided Diffusion
di: Wang, Yule, et al.
Pubblicazione: (2025)