A Stable Neural Statistical Dependence Estimator for Autoencoder Feature Analysis
Fuente:
arXiv
Saved in:
| Main Authors: | Hu, Bo, Principe, Jose C |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Normalized Cross Density Functional: A Framework to Quantify Statistical Dependence for Random Processes
by: Hu, Bo, et al.
Published: (2022)
by: Hu, Bo, et al.
Published: (2022)
Contrastive Entropy Bounds for Density and Conditional Density Decomposition
by: Hu, Bo, et al.
Published: (2025)
by: Hu, Bo, et al.
Published: (2025)
Time-Series Classification with Multivariate Statistical Dependence Features
by: Sun, Yao, et al.
Published: (2026)
by: Sun, Yao, et al.
Published: (2026)
A Simple and Effective Method for Uncertainty Quantification and OOD Detection
by: Ma, Yaxin, et al.
Published: (2025)
by: Ma, Yaxin, et al.
Published: (2025)
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
by: Rao, Xuan, et al.
Published: (2022)
by: Rao, Xuan, et al.
Published: (2022)
FaithfulSAE: Towards Capturing Faithful Features with Sparse Autoencoders without External Dataset Dependencies
by: Cho, Seonglae, et al.
Published: (2025)
by: Cho, Seonglae, et al.
Published: (2025)
Time-Aware Feature Selection: Adaptive Temporal Masking for Stable Sparse Autoencoder Training
by: Li, T. Ed, et al.
Published: (2025)
by: Li, T. Ed, et al.
Published: (2025)
Learning Multi-Level Features with Matryoshka Sparse Autoencoders
by: Bussmann, Bart, et al.
Published: (2025)
by: Bussmann, Bart, et al.
Published: (2025)
ELEMENT: Episodic and Lifelong Exploration via Maximum Entropy
by: Li, Hongming, et al.
Published: (2024)
by: Li, Hongming, et al.
Published: (2024)
Disentangled Graph Autoencoder for Treatment Effect Estimation
by: Fan, Di, et al.
Published: (2024)
by: Fan, Di, et al.
Published: (2024)
BikeVAE-GNN: A Variational Autoencoder-Augmented Hybrid Graph Neural Network for Sparse Bicycle Volume Estimation
by: Gupta, Mohit, et al.
Published: (2025)
by: Gupta, Mohit, et al.
Published: (2025)
Variational Autoencoder-Based Approach to Latent Feature Analysis on Efficient Representation of Power Load Monitoring Data
by: Xie, Boyu, et al.
Published: (2025)
by: Xie, Boyu, et al.
Published: (2025)
Autoencoding Conditional Neural Processes for Representation Learning
by: Prokhorov, Victor, et al.
Published: (2023)
by: Prokhorov, Victor, et al.
Published: (2023)
Semantic Optimal Transport for Sparse Autoencoder Feature Matching and Circuit Compression
by: Cao, Tue M., et al.
Published: (2026)
by: Cao, Tue M., et al.
Published: (2026)
Adaptive Sparse Allocation with Mutual Choice & Feature Choice Sparse Autoencoders
by: Ayonrinde, Kola
Published: (2024)
by: Ayonrinde, Kola
Published: (2024)
Meta-Statistical Learning: Supervised Learning of Statistical Estimators
by: Peyrard, Maxime, et al.
Published: (2025)
by: Peyrard, Maxime, et al.
Published: (2025)
Sparse Autoencoder Features for Classifications and Transferability
by: Gallifant, Jack, et al.
Published: (2025)
by: Gallifant, Jack, et al.
Published: (2025)
Mechanistic Interpretability as Statistical Estimation: A Variance Analysis
by: Méloux, Maxime, et al.
Published: (2025)
by: Méloux, Maxime, et al.
Published: (2025)
Feature Hedging: Correlated Features Break Narrow Sparse Autoencoders
by: Chanin, David, et al.
Published: (2025)
by: Chanin, David, et al.
Published: (2025)
Stable CDE Autoencoders with Acuity Regularization for Offline Reinforcement Learning in Sepsis Treatment
by: Gao, Yue
Published: (2025)
by: Gao, Yue
Published: (2025)
A Family of Kernelized Matrix Costs for Multiple-Output Mixture Neural Networks
by: Hu, Bo, et al.
Published: (2025)
by: Hu, Bo, et al.
Published: (2025)
Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit
by: Jiang, Nick, et al.
Published: (2025)
by: Jiang, Nick, et al.
Published: (2025)
Feature Starvation as Geometric Instability in Sparse Autoencoders
by: Chaudhry, Faris, et al.
Published: (2026)
by: Chaudhry, Faris, et al.
Published: (2026)
The Geometry of Concepts: Sparse Autoencoder Feature Structure
by: Li, Yuxiao, et al.
Published: (2024)
by: Li, Yuxiao, et al.
Published: (2024)
Mode-Dependent Rectification for Stable PPO Training
by: Mohamad, Mohamad, et al.
Published: (2026)
by: Mohamad, Mohamad, et al.
Published: (2026)
CNN Autoencoders for Hierarchical Feature Extraction and Fusion in Multi-sensor Human Activity Recognition
by: Arabzadeh, Saeed, et al.
Published: (2025)
by: Arabzadeh, Saeed, et al.
Published: (2025)
Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone
by: Bărbălau, Antonio, et al.
Published: (2025)
by: Bărbălau, Antonio, et al.
Published: (2025)
Disentangling Genotype and Environment Specific Latent Features for Improved Trait Prediction using a Compositional Autoencoder
by: Powadi, Anirudha, et al.
Published: (2024)
by: Powadi, Anirudha, et al.
Published: (2024)
Sparse Autoencoders Do Not Find Canonical Units of Analysis
by: Leask, Patrick, et al.
Published: (2025)
by: Leask, Patrick, et al.
Published: (2025)
Stabilizing Multimodal Autoencoders: A Theoretical and Empirical Analysis of Fusion Strategies
by: Altinses, Diyar, et al.
Published: (2025)
by: Altinses, Diyar, et al.
Published: (2025)
The Approximate Fisher Influence Function: Faster Estimation of Data Influence in Statistical Models
by: Lev, Omri, et al.
Published: (2024)
by: Lev, Omri, et al.
Published: (2024)
ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
by: Sauter, Andreas, et al.
Published: (2025)
by: Sauter, Andreas, et al.
Published: (2025)
Improving Steering Vectors by Targeting Sparse Autoencoder Features
by: Chalnev, Sviatoslav, et al.
Published: (2024)
by: Chalnev, Sviatoslav, et al.
Published: (2024)
Autoencoder-assisted Feature Ensemble Net for Incipient Faults
by: Gao, Mingxuan, et al.
Published: (2024)
by: Gao, Mingxuan, et al.
Published: (2024)
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network
by: Li, Bingdong, et al.
Published: (2025)
by: Li, Bingdong, et al.
Published: (2025)
On the Optimizer Dependence of Neural Scaling Laws
by: Ramani, Vansh, et al.
Published: (2026)
by: Ramani, Vansh, et al.
Published: (2026)
Does higher interpretability imply better utility? A Pairwise Analysis on Sparse Autoencoders
by: Wang, Xu, et al.
Published: (2025)
by: Wang, Xu, et al.
Published: (2025)
To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders
by: Bosello, Michael, et al.
Published: (2021)
by: Bosello, Michael, et al.
Published: (2021)
Capture Global Feature Statistics for One-Shot Federated Learning
by: Guan, Zenghao, et al.
Published: (2025)
by: Guan, Zenghao, et al.
Published: (2025)
Evaluating Feature Dependent Noise in Preference-based Reinforcement Learning
by: Li, Yuxuan, et al.
Published: (2026)
by: Li, Yuxuan, et al.
Published: (2026)
Similar Items
-
The Normalized Cross Density Functional: A Framework to Quantify Statistical Dependence for Random Processes
by: Hu, Bo, et al.
Published: (2022) -
Contrastive Entropy Bounds for Density and Conditional Density Decomposition
by: Hu, Bo, et al.
Published: (2025) -
Time-Series Classification with Multivariate Statistical Dependence Features
by: Sun, Yao, et al.
Published: (2026) -
A Simple and Effective Method for Uncertainty Quantification and OOD Detection
by: Ma, Yaxin, et al.
Published: (2025) -
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
by: Rao, Xuan, et al.
Published: (2022)