Cover Image

LatentGAN Autoencoder: Learning Disentangled Latent Distribution

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kalwar, Sanket, Aich, Animikh, Dixit, Tanay, Chhabra, Adit
Format:	Preprint
Published:	2022
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

Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
by: Hahm, Jaehoon, et al.
Published: (2024)

Disentanglement in T-space for Faster and Distributed Training of Diffusion Models with Fewer Latent-states
by: Gupta, Samarth, et al.
Published: (2025)

Shortcut Invariance: Targeted Jacobian Regularization in Disentangled Latent Space
by: Pal, Shivam, et al.
Published: (2025)

Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images
by: Zhu, Aiqing, et al.
Published: (2025)

Latent Space Characterization of Autoencoder Variants
by: Shrivastava, Anika, et al.
Published: (2024)

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

Scalable Offline Metrics for Autonomous Driving
by: Aich, Animikh, et al.
Published: (2025)

Beyond Independent Frames: Latent Attention Masked Autoencoders for Multi-View Echocardiography
by: Böhi, Simon, et al.
Published: (2026)

MIND: Decoupling Model-Induced Label Noise via Latent Manifold Disentanglement
by: Ren, Dayong
Published: (2026)

Disentangling Disentangled Representations: Towards Improved Latent Units via Diffusion Models
by: Jun, Youngjun, et al.
Published: (2024)

LSAP: Rethinking Inversion Fidelity, Perception and Editability in GAN Latent Space
by: Zhao, Xuekun, et al.
Published: (2022)

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

CAD-VAE: Leveraging Correlation-Aware Latents for Comprehensive Fair Disentanglement
by: Ma, Chenrui, et al.
Published: (2025)

i-MAE: Are Latent Representations in Masked Autoencoders Linearly Separable?
by: Zhang, Kevin, et al.
Published: (2022)

DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning
by: Bai, Sikai, et al.
Published: (2024)

Latent Diffusion Inversion Requires Understanding the Latent Space
by: Rao, Mingxing, et al.
Published: (2025)

JLT: Clean-Latent Prediction in Latent Diffusion Transformers
by: Fu, Funing, et al.
Published: (2026)

Hyperspectral Pixel Unmixing with Latent Dirichlet Variational Autoencoder
by: Mantripragada, Kiran, et al.
Published: (2022)

Disentanglement of Biological and Technical Factors via Latent Space Rotation in Clinical Imaging Improves Disease Pattern Discovery
by: Pan, Jeanny, et al.
Published: (2025)

DeepLatent: Think with Images via Parallel Latent Visual Reasoning
by: Lu, Dongchen, et al.
Published: (2026)

What's in a Latent? Leveraging Diffusion Latent Space for Domain Generalization
by: Thomas, Xavier, et al.
Published: (2025)

Probability Density from Latent Diffusion Models for Out-of-Distribution Detection
by: Järve, Joonas, et al.
Published: (2025)

SALVE: Sparse Autoencoder-Latent Vector Editing for Mechanistic Control of Neural Networks
by: Flovik, Vegard
Published: (2025)

Learning Latent Space Hierarchical EBM Diffusion Models
by: Cui, Jiali, et al.
Published: (2024)

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

Global Latent Neural Rendering
by: Tanay, Thomas, et al.
Published: (2023)

Learning Multimodal Latent Space with EBM Prior and MCMC Inference
by: Yuan, Shiyu, et al.
Published: (2024)

GLASS: Guided Latent Slot Diffusion for Object-Centric Learning
by: Singh, Krishnakant, et al.
Published: (2024)

CLA: Latent Alignment for Online Continual Self-Supervised Learning
by: Cignoni, Giacomo, et al.
Published: (2025)

Learning Multimodal Latent Generative Models with Energy-Based Prior
by: Yuan, Shiyu, et al.
Published: (2024)

VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning
by: Lin, Han, et al.
Published: (2024)

LatentHDR: Decoupling Exposure from Diffusion via Conditional Latent-to-Latent Mapping for Text/Image-to-Panoramic HDR
by: Fekri, Pedram, et al.
Published: (2026)

Steering Sparse Autoencoder Latents to Control Dynamic Head Pruning in Vision Transformers (Student Abstract)
by: Lee, Yousung, et al.
Published: (2026)

Language-Enhanced Latent Representations for Out-of-Distribution Detection in Autonomous Driving
by: Mao, Zhenjiang, et al.
Published: (2024)

Image Clustering Algorithm Based on Self-Supervised Pretrained Models and Latent Feature Distribution Optimization
by: Zhu, Qiuyu, et al.
Published: (2024)

Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection
by: Girella, Federico, et al.
Published: (2024)

CoDeGAN: Contrastive Disentanglement for Generative Adversarial Network
by: Zhao, Jiangwei, et al.
Published: (2021)

Neural Prior Estimation: Learning Class Priors from Latent Representations
by: Yavari, Masoud, et al.
Published: (2026)

Midway Network: Learning Representations for Recognition and Motion from Latent Dynamics
by: Hoang, Christopher, et al.
Published: (2025)

An Approach Towards Learning K-means-friendly Deep Latent Representation
by: Roy, Debapriya
Published: (2024)