Saved in:
| Main Author: | Schuster, Viktoria |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.11468 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can sparse autoencoders be used to decompose and interpret steering vectors?
by: Mayne, Harry, et al.
Published: (2024)
by: Mayne, Harry, et al.
Published: (2024)
Scaling and evaluating sparse autoencoders
by: Gao, Leo, et al.
Published: (2024)
by: Gao, Leo, et al.
Published: (2024)
The Deep Generative Decoder: MAP estimation of representations improves modeling of single-cell RNA data
by: Schuster, Viktoria, et al.
Published: (2021)
by: Schuster, Viktoria, et al.
Published: (2021)
Applying sparse autoencoders to unlearn knowledge in language models
by: Farrell, Eoin, et al.
Published: (2024)
by: Farrell, Eoin, et al.
Published: (2024)
Insights into a radiology-specialised multimodal large language model with sparse autoencoders
by: Bouzid, Kenza, et al.
Published: (2025)
by: Bouzid, Kenza, et al.
Published: (2025)
Decomposing multimodal embedding spaces with group-sparse autoencoders
by: Kaushik, Chiraag, et al.
Published: (2026)
by: Kaushik, Chiraag, et al.
Published: (2026)
Understanding sparse autoencoder scaling in the presence of feature manifolds
by: Michaud, Eric J., et al.
Published: (2025)
by: Michaud, Eric J., et al.
Published: (2025)
Investigating task-specific prompts and sparse autoencoders for activation monitoring
by: Tillman, Henk, et al.
Published: (2025)
by: Tillman, Henk, et al.
Published: (2025)
Theoretically informed selection of latent activation in autoencoder based recommender systems
by: Susman, Aviad
Published: (2024)
by: Susman, Aviad
Published: (2024)
Inferring stability properties of chaotic systems on autoencoders' latent spaces
by: Özalp, Elise, et al.
Published: (2024)
by: Özalp, Elise, et al.
Published: (2024)
A deep latent variable model for semi-supervised multi-unit soft sensing in industrial processes
by: Grimstad, Bjarne, et al.
Published: (2024)
by: Grimstad, Bjarne, et al.
Published: (2024)
Steering CLIP's vision transformer with sparse autoencoders
by: Joseph, Sonia, et al.
Published: (2025)
by: Joseph, Sonia, et al.
Published: (2025)
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder
by: Gupta, Priyam, et al.
Published: (2023)
by: Gupta, Priyam, et al.
Published: (2023)
Variational decomposition autoencoding improves disentanglement of latent representations
by: Ziogas, Ioannis, et al.
Published: (2026)
by: Ziogas, Ioannis, et al.
Published: (2026)
Pairwise matrices for sparse autoencoders: single-feature inspection mislabels causal axes
by: Riegler, Michael A., et al.
Published: (2026)
by: Riegler, Michael A., et al.
Published: (2026)
Variational autoencoders with latent high-dimensional steady geometric flows for dynamics
by: Gracyk, Andrew
Published: (2024)
by: Gracyk, Andrew
Published: (2024)
Ensemble Kalman filter in latent space using a variational autoencoder pair
by: Pasmans, Ivo, et al.
Published: (2025)
by: Pasmans, Ivo, et al.
Published: (2025)
Transformer autoencoder with local attention for sparse and irregular time series with application on risk estimation
by: Rodis, Panteleimon
Published: (2026)
by: Rodis, Panteleimon
Published: (2026)
An attempt to generate new bridge types from latent space of variational autoencoder
by: Zhang, Hongjun
Published: (2023)
by: Zhang, Hongjun
Published: (2023)
Computational lower bounds in latent models: clustering, sparse-clustering, biclustering
by: Even, Bertrand, et al.
Published: (2025)
by: Even, Bertrand, et al.
Published: (2025)
Target localization, identification and sensing using latent symmetries
by: Dukov, David, et al.
Published: (2026)
by: Dukov, David, et al.
Published: (2026)
Treatment response as a latent variable
by: Tosh, Christopher, et al.
Published: (2025)
by: Tosh, Christopher, et al.
Published: (2025)
Remote sensing framework for geological mapping via stacked autoencoders and clustering
by: Nagar, Sandeep, et al.
Published: (2024)
by: Nagar, Sandeep, et al.
Published: (2024)
vEEGNet: learning latent representations to reconstruct EEG raw data via variational autoencoders
by: Zancanaro, Alberto, et al.
Published: (2023)
by: Zancanaro, Alberto, et al.
Published: (2023)
Extremal graphical modeling with latent variables via convex optimization
by: Engelke, Sebastian, et al.
Published: (2024)
by: Engelke, Sebastian, et al.
Published: (2024)
Convolutional variational autoencoders for secure lossy image compression in remote sensing
by: Giuliano, Alessandro, et al.
Published: (2024)
by: Giuliano, Alessandro, et al.
Published: (2024)
Estimating treatment effects from single-arm trials via latent-variable modeling
by: Haussmann, Manuel, et al.
Published: (2023)
by: Haussmann, Manuel, et al.
Published: (2023)
Substitute adjustment via recovery of latent variables
by: Adams, Jeffrey, et al.
Published: (2024)
by: Adams, Jeffrey, et al.
Published: (2024)
SeqRisk: Transformer-augmented latent variable model for robust survival prediction with longitudinal data
by: Öğretir, Mine, et al.
Published: (2024)
by: Öğretir, Mine, et al.
Published: (2024)
On the expressivity of sparse maxout networks
by: Grillo, Moritz, et al.
Published: (2025)
by: Grillo, Moritz, et al.
Published: (2025)
Unsupervised learning of acquisition variability in structural connectomes via hybrid latent space modeling
by: Rudravaram, Gaurav, et al.
Published: (2026)
by: Rudravaram, Gaurav, et al.
Published: (2026)
A real-time anomaly detection method for robots based on a flexible and sparse latent space
by: Kang, Taewook, et al.
Published: (2025)
by: Kang, Taewook, et al.
Published: (2025)
Autosen: improving automatic wifi human sensing through cross-modal autoencoder
by: Gao, Qian, et al.
Published: (2024)
by: Gao, Qian, et al.
Published: (2024)
Variational autoencoder-based neural network model compression
by: Cheng, Liang, et al.
Published: (2024)
by: Cheng, Liang, et al.
Published: (2024)
Why should autoencoders work?
by: Kvalheim, Matthew D., et al.
Published: (2023)
by: Kvalheim, Matthew D., et al.
Published: (2023)
Identifying latent disease factors differently expressed in patient subgroups using group factor analysis
by: Ferreira, Fabio S., et al.
Published: (2024)
by: Ferreira, Fabio S., et al.
Published: (2024)
Differential equation and probability inspired graph neural networks for latent variable learning
by: Shi, Zhuangwei
Published: (2022)
by: Shi, Zhuangwei
Published: (2022)
LVM-GP: Uncertainty-Aware PDE Solver via coupling latent variable model and Gaussian process
by: Feng, Xiaodong, et al.
Published: (2025)
by: Feng, Xiaodong, et al.
Published: (2025)
Towards aerodynamic surrogate modeling based on $β$-variational autoencoders
by: Francés-Belda, Víctor, et al.
Published: (2024)
by: Francés-Belda, Víctor, et al.
Published: (2024)
Multimodal normative modeling in Alzheimers Disease with introspective variational autoencoders
by: Kumar, Sayantan, et al.
Published: (2026)
by: Kumar, Sayantan, et al.
Published: (2026)
Similar Items
-
Can sparse autoencoders be used to decompose and interpret steering vectors?
by: Mayne, Harry, et al.
Published: (2024) -
Scaling and evaluating sparse autoencoders
by: Gao, Leo, et al.
Published: (2024) -
The Deep Generative Decoder: MAP estimation of representations improves modeling of single-cell RNA data
by: Schuster, Viktoria, et al.
Published: (2021) -
Applying sparse autoencoders to unlearn knowledge in language models
by: Farrell, Eoin, et al.
Published: (2024) -
Insights into a radiology-specialised multimodal large language model with sparse autoencoders
by: Bouzid, Kenza, et al.
Published: (2025)