IBNorm: Information-Bottleneck Inspired Normalization for Representation Learning
Fuente:
arXiv
Guardado en:
| Autores principales: | Zou, Xiandong, Li, Jia, Yuan, Xiaotong, Zhou, Pan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Note on Martingale Theory and Applications
por: Zou, Xiandong
Publicado: (2026)
por: Zou, Xiandong
Publicado: (2026)
Learning Fair Graph Representations with Multi-view Information Bottleneck
por: Liu, Chuxun, et al.
Publicado: (2025)
por: Liu, Chuxun, et al.
Publicado: (2025)
Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
por: Xiong, Jiafeng, et al.
Publicado: (2025)
por: Xiong, Jiafeng, et al.
Publicado: (2025)
Dynamic Graph Information Bottleneck
por: Yuan, Haonan, et al.
Publicado: (2024)
por: Yuan, Haonan, et al.
Publicado: (2024)
Contrastive Graph Representation Learning with Adversarial Cross-view Reconstruction and Information Bottleneck
por: Shou, Yuntao, et al.
Publicado: (2024)
por: Shou, Yuntao, et al.
Publicado: (2024)
Discovering the Representation Bottleneck of Graph Neural Networks
por: Wu, Fang, et al.
Publicado: (2022)
por: Wu, Fang, et al.
Publicado: (2022)
A Distance Metric Learning Model Based On Variational Information Bottleneck
por: Zhang, YaoDan, et al.
Publicado: (2024)
por: Zhang, YaoDan, et al.
Publicado: (2024)
Eliminating Information Leakage in Hard Concept Bottleneck Models with Supervised, Hierarchical Concept Learning
por: Sun, Ao, et al.
Publicado: (2024)
por: Sun, Ao, et al.
Publicado: (2024)
Will More Expressive Graph Neural Networks do Better on Generative Tasks?
por: Zou, Xiandong, et al.
Publicado: (2023)
por: Zou, Xiandong, et al.
Publicado: (2023)
Enhancing Adversarial Transferability via Information Bottleneck Constraints
por: Qi, Biqing, et al.
Publicado: (2024)
por: Qi, Biqing, et al.
Publicado: (2024)
MemFly: On-the-Fly Memory Optimization via Information Bottleneck
por: Zhang, Zhenyuan, et al.
Publicado: (2026)
por: Zhang, Zhenyuan, et al.
Publicado: (2026)
TimeX++: Learning Time-Series Explanations with Information Bottleneck
por: Liu, Zichuan, et al.
Publicado: (2024)
por: Liu, Zichuan, et al.
Publicado: (2024)
Conda: Column-Normalized Adam for Training Large Language Models Faster
por: Wang, Junjie, et al.
Publicado: (2025)
por: Wang, Junjie, et al.
Publicado: (2025)
nGPT: Normalized Transformer with Representation Learning on the Hypersphere
por: Loshchilov, Ilya, et al.
Publicado: (2024)
por: Loshchilov, Ilya, et al.
Publicado: (2024)
TimeSieve: Extracting Temporal Dynamics through Information Bottlenecks
por: Feng, Ninghui, et al.
Publicado: (2024)
por: Feng, Ninghui, et al.
Publicado: (2024)
GaGSL: Global-augmented Graph Structure Learning via Graph Information Bottleneck
por: Li, Shuangjie, et al.
Publicado: (2024)
por: Li, Shuangjie, 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)
Learning to Intervene on Concept Bottlenecks
por: Steinmann, David, et al.
Publicado: (2023)
por: Steinmann, David, et al.
Publicado: (2023)
Glocal Information Bottleneck for Time Series Imputation
por: Yang, Jie, et al.
Publicado: (2025)
por: Yang, Jie, et al.
Publicado: (2025)
Causally-Aware Information Bottleneck for Domain Adaptation
por: Javidian, Mohammad Ali
Publicado: (2026)
por: Javidian, Mohammad Ali
Publicado: (2026)
Interpretable Prototype-based Graph Information Bottleneck
por: Seo, Sangwoo, et al.
Publicado: (2023)
por: Seo, Sangwoo, et al.
Publicado: (2023)
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
por: Federici, Marco, et al.
Publicado: (2023)
por: Federici, Marco, et al.
Publicado: (2023)
Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning
por: Zhou, Yang, et al.
Publicado: (2025)
por: Zhou, Yang, et al.
Publicado: (2025)
IIB-LPO: Latent Policy Optimization via Iterative Information Bottleneck
por: Deng, Huilin, et al.
Publicado: (2026)
por: Deng, Huilin, et al.
Publicado: (2026)
XFACTORS: Disentangled Information Bottleneck via Contrastive Supervision
por: Myara, Alexandre, et al.
Publicado: (2026)
por: Myara, Alexandre, et al.
Publicado: (2026)
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection
por: Chen, Yutong, et al.
Publicado: (2024)
por: Chen, Yutong, et al.
Publicado: (2024)
RED: Effective Trajectory Representation Learning with Comprehensive Information
por: Zhou, Silin, et al.
Publicado: (2024)
por: Zhou, Silin, et al.
Publicado: (2024)
Generative Distribution Prediction: A Unified Approach to Multimodal Learning
por: Tian, Xinyu, et al.
Publicado: (2025)
por: Tian, Xinyu, et al.
Publicado: (2025)
AGHINT: Attribute-Guided Representation Learning on Heterogeneous Information Networks with Transformer
por: Yuan, Jinhui, et al.
Publicado: (2024)
por: Yuan, Jinhui, et al.
Publicado: (2024)
Incremental Residual Concept Bottleneck Models
por: Shang, Chenming, et al.
Publicado: (2024)
por: Shang, Chenming, et al.
Publicado: (2024)
SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding
por: Zhou, Yangxuan, et al.
Publicado: (2025)
por: Zhou, Yangxuan, et al.
Publicado: (2025)
Breaking the Context Bottleneck on Long Time Series Forecasting
por: Ma, Chao, et al.
Publicado: (2024)
por: Ma, Chao, et al.
Publicado: (2024)
A Human-Inspired Decoupled Architecture for Efficient Audio Representation Learning
por: Kawano, Harunori, et al.
Publicado: (2026)
por: Kawano, Harunori, et al.
Publicado: (2026)
Exploring Dynamic Properties of Backdoor Training Through Information Bottleneck
por: Liu, Xinyu, et al.
Publicado: (2025)
por: Liu, Xinyu, et al.
Publicado: (2025)
DDTime: Dataset Distillation with Spectral Alignment and Information Bottleneck for Time-Series Forecasting
por: Li, Yuqi, et al.
Publicado: (2025)
por: Li, Yuqi, et al.
Publicado: (2025)
Unlearning Information Bottleneck: Machine Unlearning of Systematic Patterns and Biases
por: Han, Ling, et al.
Publicado: (2024)
por: Han, Ling, et al.
Publicado: (2024)
Learning Concept Bottleneck Models from Mechanistic Explanations
por: De Santis, Antonio, et al.
Publicado: (2026)
por: De Santis, Antonio, et al.
Publicado: (2026)
Is Value Learning Really the Main Bottleneck in Offline RL?
por: Park, Seohong, et al.
Publicado: (2024)
por: Park, Seohong, et al.
Publicado: (2024)
Neuro-Inspired Hierarchical Multimodal Learning
por: Xiao, Xiongye, et al.
Publicado: (2023)
por: Xiao, Xiongye, et al.
Publicado: (2023)
Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics
por: Zhang, Xinyu, et al.
Publicado: (2024)
por: Zhang, Xinyu, et al.
Publicado: (2024)
Ejemplares similares
-
Note on Martingale Theory and Applications
por: Zou, Xiandong
Publicado: (2026) -
Learning Fair Graph Representations with Multi-view Information Bottleneck
por: Liu, Chuxun, et al.
Publicado: (2025) -
Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
por: Xiong, Jiafeng, et al.
Publicado: (2025) -
Dynamic Graph Information Bottleneck
por: Yuan, Haonan, et al.
Publicado: (2024) -
Contrastive Graph Representation Learning with Adversarial Cross-view Reconstruction and Information Bottleneck
por: Shou, Yuntao, et al.
Publicado: (2024)