EdVAE: Mitigating Codebook Collapse with Evidential Discrete Variational Autoencoders

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Baykal, Gulcin, Kandemir, Melih, Unal, Gozde
Format:	Preprint
Published:	2023
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Disentanglement with Factor Quantized Variational Autoencoders
by: Baykal, Gulcin, et al.
Published: (2024)

Calibrating Bayesian UNet++ for Sub-Seasonal Forecasting
by: Asan, Busra, et al.
Published: (2024)

PCA-VAE: Differentiable Subspace Quantization without Codebook Collapse
by: Lu, Hao, et al.
Published: (2026)

Overcoming Non-stationary Dynamics with Evidential Proximal Policy Optimization
by: Akgül, Abdullah, et al.
Published: (2025)

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

VAE-QWGAN: Addressing Mode Collapse in Quantum GANs via Autoencoding Priors
by: Thomas, Aaron Mark, et al.
Published: (2024)

Policy-based Tuning of Autoregressive Image Models with Instance- and Distribution-Level Rewards
by: Baran, Orhun Buğra, et al.
Published: (2026)

The Gaussian Discriminant Variational Autoencoder (GdVAE): A Self-Explainable Model with Counterfactual Explanations
by: Haselhoff, Anselm, et al.
Published: (2024)

HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes
by: Takida, Yuhta, et al.
Published: (2023)

Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling
by: Xie, Tianyu, et al.
Published: (2025)

Multivariate Variational Autoencoder
by: Yavuz, Mehmet Can
Published: (2025)

L-VAE: Variational Auto-Encoder with Learnable Beta for Disentangled Representation
by: Ozcan, Hazal Mogultay, et al.
Published: (2025)

Branched Variational Autoencoder Classifiers
by: Salah, Ahmed, et al.
Published: (2024)

Graph Attention Neural Network for Botnet Detection: Evaluating Autoencoder, VAE and PCA-Based Dimension Reduction
by: Wasswa, Hassan, et al.
Published: (2025)

Continual Learning of Multi-modal Dynamics with External Memory
by: Akgül, Abdullah, et al.
Published: (2022)

VIVAT: Virtuous Improving VAE Training through Artifact Mitigation
by: Novitskiy, Lev, et al.
Published: (2025)

Variational Autoencoding of Dental Point Clouds
by: Ye, Johan Ziruo, et al.
Published: (2023)

Spherical VAE with Cluster-Aware Feasible Regions: Guaranteed Prevention of Posterior Collapse
by: Zhang, Zegu, et al.
Published: (2026)

Analyzing and Mitigating Model Collapse in Rectified Flow Models
by: Zhu, Huminhao, et al.
Published: (2024)

Pairing Regularization for Mitigating Many-to-One Collapse in GANs
by: Lin, Kuan-Yu, et al.
Published: (2026)

An Elastic Shape Variational Autoencoder for Skeleton Pose Trajectories
by: Rahman, Arafat, et al.
Published: (2026)

SepVAE: a contrastive VAE to separate pathological patterns from healthy ones
by: Louiset, Robin, et al.
Published: (2023)

Variational Autoencoder Framework for Hyperspectral Retrievals (Hyper-VAE) of Phytoplankton Absorption and Chlorophyll a in Coastal Waters for NASA's EMIT and PACE Missions
by: Lou, Jiadong, et al.
Published: (2025)

Uncertainty-Supervised Interpretable and Robust Evidential Segmentation
by: Li, Yuzhu, et al.
Published: (2025)

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection
by: Orglmeister, Conrad, et al.
Published: (2025)

Entropy Minimization without Model Collapse: Mitigating Prediction Bias in Medical Imaging
by: Nielen, Tim, et al.
Published: (2026)

Unsupervised Multiple Domain Translation through Controlled Disentanglement in Variational Autoencoder
by: Almudévar, Antonio, et al.
Published: (2024)

Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection
by: Suvon, Mohammod N. I., et al.
Published: (2024)

A Note on Generalization in Variational Autoencoders: How Effective Is Synthetic Data & Overparameterization?
by: Xiao, Tim Z., et al.
Published: (2023)

Quantize-then-Rectify: Efficient VQ-VAE Training
by: Zhang, Borui, et al.
Published: (2025)

GenZSL: Generative Zero-Shot Learning Via Inductive Variational Autoencoder
by: Chen, Shiming, et al.
Published: (2025)

Out-of-Distribution Segmentation via Wasserstein-Based Evidential Uncertainty
by: Brosch, Arnold, et al.
Published: (2025)

Cross-Dataset Gaze Estimation by Evidential Inter-intra Fusion
by: Wang, Shijing, et al.
Published: (2024)

Generalized Evidential Deep Learning: From a Bayesian Perspective
by: Liu, Yuanye, et al.
Published: (2026)

Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
by: Li, Changbin, et al.
Published: (2024)

Device Image-IV Mapping using Variational Autoencoder for Inverse Design and Forward Prediction
by: Lu, Thomas, et al.
Published: (2023)

Style Feature Extraction Using Contrastive Conditioned Variational Autoencoders with Mutual Information Constraints
by: Yasutomi, Suguru, et al.
Published: (2023)

Curvature-Regularized Variational Autoencoder for 3D Scene Reconstruction from Sparse Depth
by: Yousefi, Maryam, et al.
Published: (2025)

Evidential Neural Radiance Fields
by: Duan, Ruxiao, et al.
Published: (2026)

Multimodal Variational Autoencoder: a Barycentric View
by: Qiu, Peijie, et al.
Published: (2024)