Identifiable Deep Generative Models via Sparse Decoding
Fuente:
arXiv
Saved in:
| Main Authors: | Moran, Gemma E., Sridhar, Dhanya, Wang, Yixin, Blei, David M. |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards Interpretable Deep Generative Models via Causal Representation Learning
by: Moran, Gemma E., et al.
Published: (2025)
by: Moran, Gemma E., et al.
Published: (2025)
Optimization-based Causal Estimation from Heterogenous Environments
by: Yin, Mingzhang, et al.
Published: (2021)
by: Yin, Mingzhang, et al.
Published: (2021)
Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes
by: Wu, Bohan, et al.
Published: (2024)
by: Wu, Bohan, et al.
Published: (2024)
Neural Generalized Mixed-Effects Models
by: Slavutsky, Yuli, et al.
Published: (2026)
by: Slavutsky, Yuli, et al.
Published: (2026)
Hierarchical Causal Models
by: Weinstein, Eli N., et al.
Published: (2024)
by: Weinstein, Eli N., et al.
Published: (2024)
Estimating Wage Disparities Using Foundation Models
by: Vafa, Keyon, et al.
Published: (2024)
by: Vafa, Keyon, et al.
Published: (2024)
Multi-Domain Empirical Bayes for Linearly-Mixed Causal Representations
by: Wu, Bohan, et al.
Published: (2026)
by: Wu, Bohan, et al.
Published: (2026)
Bayesian Empirical Bayes: Simultaneous Inference from Probabilistic Symmetries
by: Wu, Bohan, et al.
Published: (2025)
by: Wu, Bohan, et al.
Published: (2025)
Stable Differentiable Causal Discovery
by: Nazaret, Achille, et al.
Published: (2023)
by: Nazaret, Achille, et al.
Published: (2023)
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
by: Brouillard, Philippe, et al.
Published: (2024)
by: Brouillard, Philippe, et al.
Published: (2024)
Toward the Identifiability of Comparative Deep Generative Models
by: Lopez, Romain, et al.
Published: (2024)
by: Lopez, Romain, et al.
Published: (2024)
Evaluating Interventional Reasoning Capabilities of Large Language Models
by: Kasetty, Tejas, et al.
Published: (2024)
by: Kasetty, Tejas, et al.
Published: (2024)
Identifiable Deep Latent Variable Models for MNAR Data
by: Xie, Huiming, et al.
Published: (2026)
by: Xie, Huiming, et al.
Published: (2026)
Deep Discrete Encoders: Identifiable Deep Generative Models for Rich Data with Discrete Latent Layers
by: Lee, Seunghyun, et al.
Published: (2025)
by: Lee, Seunghyun, et al.
Published: (2025)
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
by: Thompson, Ryan, et al.
Published: (2023)
by: Thompson, Ryan, et al.
Published: (2023)
Worst-case low-rank approximations
by: Fries, Anya, et al.
Published: (2026)
by: Fries, Anya, et al.
Published: (2026)
Generalized Criterion for Identifiability of Additive Noise Models Using Majorization
by: Dallakyan, Aramayis, et al.
Published: (2024)
by: Dallakyan, Aramayis, et al.
Published: (2024)
Sparse Shift Autoencoders for Identifying Concepts from Large Language Model Activations
by: Joshi, Shruti, et al.
Published: (2025)
by: Joshi, Shruti, et al.
Published: (2025)
Environment-Adaptive Covariate Selection: Learning When to Use Spurious Correlations for Out-of-Distribution Prediction
by: Zuo, Shuozhi, et al.
Published: (2026)
by: Zuo, Shuozhi, et al.
Published: (2026)
Optimal Sampling for Generalized Linear Model under Measurement Constraint with Surrogate Variables
by: Shen, Yixin, et al.
Published: (2025)
by: Shen, Yixin, et al.
Published: (2025)
Conditional Rank-Rank Regression via Deep Conditional Transformation Models
by: Wang, Xiaoyi, et al.
Published: (2026)
by: Wang, Xiaoyi, et al.
Published: (2026)
Identifiability of Sparse Causal Effects using Instrumental Variables
by: Pfister, Niklas, et al.
Published: (2022)
by: Pfister, Niklas, et al.
Published: (2022)
Sparse Equation Matching: A Derivative-Free Learning for General-Order Dynamical Systems
by: Li, Jiaqiang, et al.
Published: (2025)
by: Li, Jiaqiang, et al.
Published: (2025)
Discrete Causal Representation Learning
by: Zhang, Wenjin, et al.
Published: (2026)
by: Zhang, Wenjin, et al.
Published: (2026)
Towards Identifiable Latent Additive Noise Models
by: Liu, Yuhang, et al.
Published: (2024)
by: Liu, Yuhang, et al.
Published: (2024)
Estimand framework and intercurrent events handling for clinical trials with time-to-event outcomes
by: Fang, Yixin, et al.
Published: (2025)
by: Fang, Yixin, et al.
Published: (2025)
A Targeted Learning Framework for Estimating Restricted Mean Survival Time Difference using Pseudo-observations
by: Jin, Man, et al.
Published: (2026)
by: Jin, Man, et al.
Published: (2026)
Arbitrated Indirect Treatment Comparisons
by: Fang, Yixin, et al.
Published: (2025)
by: Fang, Yixin, et al.
Published: (2025)
Flexible Clustering with a Sparse Mixture of Generalized Hyperbolic Distributions
by: Sochaniwsky, Alexa A., et al.
Published: (2019)
by: Sochaniwsky, Alexa A., et al.
Published: (2019)
Latency-Response Theory Model: Evaluating Large Language Models via Response Accuracy and Chain-of-Thought Length
by: Xu, Zhiyu, et al.
Published: (2025)
by: Xu, Zhiyu, et al.
Published: (2025)
Modeling Nonstationary Extremal Dependence via Deep Spatial Deformations
by: Shao, Xuanjie, et al.
Published: (2025)
by: Shao, Xuanjie, et al.
Published: (2025)
On the Parameter Identifiability of Partially Observed Linear Causal Models
by: Dong, Xinshuai, et al.
Published: (2024)
by: Dong, Xinshuai, et al.
Published: (2024)
Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families
by: Hulsman, Roel, et al.
Published: (2026)
by: Hulsman, Roel, et al.
Published: (2026)
Sparse Asymptotic PCA: Identifying Sparse Latent Factors Across Time Horizon in High-Dimensional Time Series
by: Gao, Zhaoxing
Published: (2024)
by: Gao, Zhaoxing
Published: (2024)
A Flexible Empirical Bayes Approach to Generalized Linear Models, with Applications to Sparse Logistic Regression
by: Xie, Dongyue, et al.
Published: (2026)
by: Xie, Dongyue, et al.
Published: (2026)
Valid Inference After Causal Discovery
by: Gradu, Paula, et al.
Published: (2022)
by: Gradu, Paula, et al.
Published: (2022)
Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives
by: Behdin, Kayhan, et al.
Published: (2023)
by: Behdin, Kayhan, et al.
Published: (2023)
Automatic Change-Point Detection in Time Series via Deep Learning
by: Li, Jie, et al.
Published: (2022)
by: Li, Jie, et al.
Published: (2022)
Fitting Sparse Markov Models to Categorical Time Series Using Convex Clustering
by: Majumder, Tuhin, et al.
Published: (2022)
by: Majumder, Tuhin, et al.
Published: (2022)
Proximal Projection for Doubly Sparse Regularized Models
by: He, Jia Wei, et al.
Published: (2026)
by: He, Jia Wei, et al.
Published: (2026)
Similar Items
-
Towards Interpretable Deep Generative Models via Causal Representation Learning
by: Moran, Gemma E., et al.
Published: (2025) -
Optimization-based Causal Estimation from Heterogenous Environments
by: Yin, Mingzhang, et al.
Published: (2021) -
Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes
by: Wu, Bohan, et al.
Published: (2024) -
Neural Generalized Mixed-Effects Models
by: Slavutsky, Yuli, et al.
Published: (2026) -
Hierarchical Causal Models
by: Weinstein, Eli N., et al.
Published: (2024)