:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Ruffenach, Yves
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2512.24102
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Latent-Autoregressive GP-VAE Language Model
by: Ruffenach, Yves
Published: (2025)

Agentic Control in Variational Language Models
by: Ruffenach, Yves
Published: (2026)

Variational Neurons in Transformers for Language Modeling
by: Ruffenach, Yves
Published: (2026)

Exploring the Dimensions of a Variational Neuron
by: Ruffenach, Yves
Published: (2026)

Variational Distributional Neuron
by: Ruffenach, Yves
Published: (2026)

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
by: Kouzelis, Theodoros, et al.
Published: (2025)

Structured Kernel Regression VAE: A Computationally Efficient Surrogate for GP-VAEs in ICA
by: Wei, Yuan-Hao, et al.
Published: (2025)

Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
by: Rozet, François, et al.
Published: (2025)

Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE Model
by: Slautin, Boris N., et al.
Published: (2025)

Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spaces
by: Elabid, Zakaria, et al.
Published: (2026)

VAE with Hyperspherical Coordinates: Improving Anomaly Detection from Hypervolume-Compressed Latent Space
by: Ascarate, Alejandro, et al.
Published: (2026)

A Unified Latent Space Disentanglement VAE Framework with Robust Disentanglement Effectiveness Evaluation
by: Lang, Xiaoan, et al.
Published: (2026)

How Neural Losses Shape VAE Latents
by: Strano, Giorgio, et al.
Published: (2026)

Shared Latent Space by Both Languages in Non-Autoregressive Neural Machine Translation
by: Heo, DongNyeong, et al.
Published: (2023)

Improved Anomaly Detection through Conditional Latent Space VAE Ensembles
by: Åström, Oskar, et al.
Published: (2024)

Leveraging VAE-Derived Latent Spaces for Enhanced Malware Detection with Machine Learning Classifiers
by: Ajayi, Bamidele, et al.
Published: (2025)

CircuitVAE: Efficient and Scalable Latent Circuit Optimization
by: Song, Jialin, et al.
Published: (2024)

Impact of Latent Space Dimension on IoT Botnet Detection Performance: VAE-Encoder Versus ViT-Encoder
by: Wasswa, Hassan, et al.
Published: (2025)

VQalAttent: a Transparent Speech Generation Pipeline based on Transformer-learned VQ-VAE Latent Space
by: Rodriguez, Armani, et al.
Published: (2024)

FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
by: Hu, Chen, et al.
Published: (2024)

LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models
by: Sadat, Seyedmorteza, et al.
Published: (2024)

On the Shape of Latent Variables in a Denoising VAE-MoG: A Posterior Sampling-Based Study
by: Bascuñán, Fernanda Zapata
Published: (2025)

HiVAE: Hierarchical Latent Variables for Scalable Theory of Mind
by: Doering, Nigel, et al.
Published: (2026)

Projected Autoregression: Autoregressive Language Generation in Continuous State Space
by: Naparstek, Oshri
Published: (2026)

Unsupervised Anomaly Detection in NSL-KDD Using $β$-VAE: A Latent Space and Reconstruction Error Approach
by: Baptiste, Dylan, et al.
Published: (2026)

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models
by: Bi, Tianci, et al.
Published: (2025)

An Invariant Latent Space Perspective on Language Model Inversion
by: Ye, Wentao, et al.
Published: (2025)

AR-Flow VAE: A Structured Autoregressive Flow Prior Variational Autoencoder for Unsupervised Blind Source Separation
by: Wei, Yuan-Hao, et al.
Published: (2026)

Fast Autoregressive Models for Continuous Latent Generation
by: Hang, Tiankai, et al.
Published: (2025)

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows
by: Zhang, Ruixiang, et al.
Published: (2025)

ARD-VAE: A Statistical Formulation to Find the Relevant Latent Dimensions of Variational Autoencoders
by: Saha, Surojit, et al.
Published: (2025)

Less Is More: Generating Time Series with LLaMA-Style Autoregression in Simple Factorized Latent Spaces
by: Li, Siyuan, et al.
Published: (2025)

Multi-scale Autoregressive Models are Laplacian, Discrete, and Latent Diffusion Models in Disguise
by: Hong, Steve, et al.
Published: (2025)

STAR-VAE: Latent Variable Transformers for Scalable and Controllable Molecular Generation
by: Kwon, Bum Chul, et al.
Published: (2025)

Recursive Inference for Heterogeneous Multi-Output GP State-Space Models with Arbitrary Moment Matching
by: Zheng, Tengjie, et al.
Published: (2025)

Structural Equation-VAE: Disentangled Latent Representations for Tabular Data
by: Zhang, Ruiyu, et al.
Published: (2025)

Uncovering Population PK Covariates from VAE-Generated Latent Spaces
by: Perazzolo, Diego, et al.
Published: (2025)

Parallelizing Autoregressive Generation with Variational State Space Models
by: Lambrechts, Gaspard, et al.
Published: (2024)

Latent-DARM: Bridging Discrete Diffusion And Autoregressive Models For Reasoning
by: Berrayana, Lina, et al.
Published: (2026)

Half-VAE: An Encoder-Free VAE to Bypass Explicit Inverse Mapping
by: Wei, Yuan-Hao, et al.
Published: (2024)