variational autoencoder

BETA: Resting-state fMRI Biotypes for tDCS Efficacy in Anxiety Among Older Adults At Risk For Alzheimer’s Disease MIDL 2026 Beyond Mean-Field: Tree-Copula Variational Autoencoders for Structured Latent Dependencies UAI 2026 BridgeShape: Latent Diffusion Schrödinger Bridge for 3D Shape Completion AAAI 2026 CAD-VAE: Leveraging Correlation-Aware Latents for Comprehensive Fair Disentanglement AAAI 2026 Causal Motion Diffusion Models for Autoregressive Motion Generation CVPR 2026 CoGenSAM: Codebook-Interactive Generative Labeling for Adapting SAM to Crack Segmentation AAAI 2026 Content-Aware Dynamic Patchification for Efficient Video Diffusion CVPR 2026 Continual Learning for fMRI-Based Brain Disorder Diagnosis via Functional Connectivity Matrices Generative Replay CVPR 2026 Controllable Long-term Motion Generation with Extended Joint Targets WACV 2026 Correcting Quantization-Induced Gradient Mismatch in Neural Image Compression AAAI 2026 D3-RSMDE: 40× Faster and High-Fidelity Remote Sensing Monocular Depth Estimation AAAI 2026 DA-VAE: Plug-in Latent Compression for Diffusion via Detail Alignment CVPR 2026 Debiased Cognitive Diagnosis: A Contrastive Counterfactual Modeling Method via Variational Autoencoder AAAI 2026 DiA-gnostic VLVAE: Disentangled Alignment-Constrained Vision Language Variational AutoEncoder for Robust Radiology Reporting with Missing Modalities AAAI 2026 Discovering Mixture Skills for Unsupervised Reinforcement Learning AAAI 2026 Discrete Facial Encoding: A Framework for Data-driven Facial Display Discovery WACV 2026 Disentangling Emotion Understanding and Generation in Large Language Models EACL 2026 EA-VAE: Learning to Reconstruct Dysarthric Speech via Variational Autoencoder with Encoding Alignment AAAI 2026 Elastic3D: Controllable Stereo Video Conversion with Guided Latent Decoding CVPR 2026 Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI ACL 2026 Explainable Pathomics Feature Visualization via Correlation-aware Conditional Feature Editing MIDL 2026 Explore to Learn: Latent Exploration Through Disentangled Synergy Patterns for Reinforcement Learning in Overactuated Control AAAI 2026 FedAU2: Attribute Unlearning for User-Level Federated Recommender Systems with Adaptive and Robust Adversarial Training AAAI 2026 Fidelity-Aware Recommendation Explanations via Stochastic Path Integration AAAI 2026 From Cross-Sectional CT to Dynamic Insights: Pseudotime-Based Modeling of Lung Nodule Progression MIDL 2026