:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Oubari, Fouad, El-Baha, Mohamed, Meunier, Raphael, Décatoire, Rodrigue, Mougeot, Mathilde
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2507.12165
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Markov Random Field Multi-Modal Variational AutoEncoder
by: Oubari, Fouad, et al.
Published: (2024)

Deep Generative Methods and Tire Architecture Design
by: Oubari, Fouad, et al.
Published: (2025)

Correcting Source Mismatch in Flow Matching with Radial-Angular Transport
by: Oubari, Fouad, et al.
Published: (2026)

Geometry-aware framework for deep energy method: an application to structural mechanics with hyperelastic materials
by: Nguyen, Thi Nguyen Khoa, et al.
Published: (2024)

Fixed-budget online adaptive learning for physics-informed neural networks. Towards parameterized problem inference
by: Nguyen, Thi Nguyen Khoa, et al.
Published: (2022)

Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
by: de Mathelin, Antoine, et al.
Published: (2023)

Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems
by: Lippert, Fiona, et al.
Published: (2023)

Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees
by: Jaber, Edgar, et al.
Published: (2024)

Simple, Fast and Efficient Injective Manifold Density Estimation with Random Projections
by: Amin, Ahmad Ayaz, et al.
Published: (2025)

BN-SCAFFOLD: controlling the drift of Batch Normalization statistics in Federated Learning
by: Quintana, Gonzalo Iñaki, et al.
Published: (2024)

Cascaded Transfer: Learning Many Tasks under Budget Constraints
by: Campagne, Eloi, et al.
Published: (2026)

Flexible and Efficient Probabilistic PDE Solvers through Gaussian Markov Random Fields
by: Weiland, Tim, et al.
Published: (2025)

OneBatchPAM: A Fast and Frugal K-Medoids Algorithm
by: de Mathelin, Antoine, et al.
Published: (2025)

Bridging Contrastive Learning and Domain Adaptation: Theoretical Perspective and Practical Application
by: Quintana, Gonzalo Iñaki, et al.
Published: (2025)

GaussianVAE: Adaptive Learning Dynamics of 3D Gaussians for High-Fidelity Super-Resolution
by: Khalid, Shuja, et al.
Published: (2025)

Learning Juntas under Markov Random Fields
by: Chandrasekaran, Gautam, et al.
Published: (2025)

Adaptive Mean Estimation in the Hidden Markov sub-Gaussian Mixture Model
by: Karagulyan, Vahe, et al.
Published: (2024)

Colored Markov Random Fields for Probabilistic Topological Modeling
by: Marinucci, Lorenzo, et al.
Published: (2025)

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

Physically Interpretable Representation Learning with Gaussian Mixture Variational AutoEncoder (GM-VAE)
by: Fan, Tiffany, et al.
Published: (2025)

High-dimensional Inference and FDR Control for Simulated Markov Random Fields
by: Wei, Haoyu, et al.
Published: (2022)

VAE for Modified 1-Hot Generative Materials Modeling, A Step Towards Inverse Material Design
by: El-Awady, Khalid
Published: (2023)

GQ-VAE: A gated quantized VAE for learning variable length tokens
by: Datta, Theo, et al.
Published: (2025)

SAHMM-VAE: A Source-Wise Adaptive Hidden Markov Prior Variational Autoencoder for Unsupervised Blind Source Separation
by: Wei, Yuan-Hao
Published: (2026)

Sparse Interaction Neighborhood Selection for Markov Random Fields via Reversible Jump and Pseudoposteriors
by: Freguglia, Victor, et al.
Published: (2022)

TripOptimizer: Generative 3D Shape Optimization and Drag Prediction using Triplane VAE Networks
by: Vatani, Parsa, et al.
Published: (2025)

MO-RiskVAE: A Multi-Omics Variational Autoencoder for Survival Risk Modeling in Multiple MyelomaMO-RiskVAE
by: Chen, Zixuan, et al.
Published: (2026)

Half-AVAE: Adversarial-Enhanced Factorized and Structured Encoder-Free VAE for Underdetermined Independent Component Analysis
by: Wei, Yuan-Hao, et al.
Published: (2025)

The Temporal Markov Transition Field
by: Leznik, Michael
Published: (2026)

Random ReLU Neural Networks as Non-Gaussian Processes
by: Parhi, Rahul, et al.
Published: (2024)

Beta-Sigma VAE: Separating beta and decoder variance in Gaussian variational autoencoder
by: Kim, Seunghwan, et al.
Published: (2024)

Density-Informed VAE (DiVAE): Reliable Log-Prior Probability via Density Alignment Regularization
by: Alessi, Michele, et al.
Published: (2025)

How Does Attention Help? Insights from Random Matrices on Signal Recovery from Sequence Models
by: Seddik, Mohamed El Amine
Published: (2026)

PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors for Nonlinear ICA
by: Wei, Yuan-Hao, et al.
Published: (2026)

Comparative Analysis of MDL-VAE vs. Standard VAE on 202 Years of Gynecological Data
by: Santos, Paula
Published: (2025)

AI Agents Need Memory Control Over More Context
by: Bousetouane, Fouad
Published: (2026)

ReMAP: Neural Reparameterization for Scalable MAP Inference in Arbitrary-Order Markov Random Fields
by: Wang, Yaomin, et al.
Published: (2024)

Iterative Amortized Hierarchical VAE
by: Penninga, Simon W., et al.
Published: (2026)

LakotaBERT: A Transformer-based Model for Low Resource Lakota Language
by: Parankusham, Kanishka, et al.
Published: (2025)

Toward Carbon-Neutral Human AI: Rethinking Data, Computation, and Learning Paradigms for Sustainable Intelligence
by: Santosh, KC, et al.
Published: (2025)