{"total":49,"rows":[{"id":"2503.15451","title":"MotionStreamer: Streaming Motion Generation via Diffusion-based Autoregressive Model in Causal Latent Space","created":"2025-03-19","cited_by_count":86,"area":null},{"id":"2309.08480","title":"PoseFix: Correcting 3D Human Poses with Natural Language","created":"2023-09-15","cited_by_count":40,"area":null},{"id":"2206.02416","title":"Embrace the Gap: VAEs Perform Independent Mechanism Analysis","created":"2022-06-06","cited_by_count":28,"area":null},{"id":"2212.03905","title":"Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve","created":"2022-12-07","cited_by_count":18,"area":null},{"id":"2210.11795","title":"PoseScript: Linking 3D Human Poses and Natural Language","created":"2022-10-21","cited_by_count":14,"area":null},{"id":"2208.04589","title":"Long-term Causal Effects Estimation via Latent Surrogates Representation Learning","created":"2022-08-09","cited_by_count":12,"area":null},{"id":"2402.07577","title":"Topic Modeling as Multi-Objective Contrastive Optimization","created":"2024-02-12","cited_by_count":12,"area":null},{"id":"2112.14278","title":"Beta-VAE Reproducibility: Challenges and Extensions","created":"2021-12-28","cited_by_count":10,"area":null},{"id":"2110.11435","title":"Generating Multivariate Load States Using a Conditional Variational Autoencoder","created":"2021-10-21","cited_by_count":8,"area":null},{"id":"2203.10528","title":"Stochastic Video Prediction with Structure and Motion","created":"2022-03-20","cited_by_count":8,"area":null},{"id":"2203.15210","title":"Camera-Conditioned Stable Feature Generation for Isolated Camera Supervised Person Re-IDentification","created":"2022-03-29","cited_by_count":8,"area":null},{"id":"2207.01845","title":"Planning with RL and episodic-memory behavioral priors","created":"2022-07-05","cited_by_count":8,"area":null},{"id":"2210.16844","title":"Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders","created":"2022-10-30","cited_by_count":8,"area":null},{"id":"2209.07007","title":"Gromov-Wasserstein Autoencoders","created":"2022-09-15","cited_by_count":7,"area":null},{"id":"2106.13739","title":"Re-parameterizing VAEs for stability","created":"2021-06-25","cited_by_count":6,"area":null},{"id":"2304.04307","title":"PriorCVAE: scalable MCMC parameter inference with Bayesian deep generative modelling","created":"2023-04-09","cited_by_count":6,"area":null},{"id":"2311.07693","title":"Matching aggregate posteriors in the variational autoencoder","created":"2023-11-13","cited_by_count":6,"area":null},{"id":"2309.07663","title":"High-dimensional Asymptotics of VAEs: Threshold of Posterior Collapse and Dataset-Size Dependence of Rate-Distortion Curve","created":"2023-09-14","cited_by_count":5,"area":null},{"id":"2211.15053","title":"Distinguishing representational geometries with controversial stimuli: Bayesian experimental design and its application to face dissimilarity judgments","created":"2022-11-28","cited_by_count":4,"area":null},{"id":"2404.15390","title":"Remedying uncertainty representations in visual inference through Explaining-Away Variational Autoencoders","created":"2024-04-23","cited_by_count":4,"area":null},{"id":"2403.14682","title":"Deep Generative Domain Adaptation with Temporal Relation Knowledge for Cross-User Activity Recognition","created":"2024-03-12","cited_by_count":3,"area":null},{"id":"2403.17958","title":"Deep Generative Domain Adaptation with Temporal Attention for Cross-User Activity Recognition","created":"2024-03-12","cited_by_count":3,"area":null},{"id":"2408.05834","title":"Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm","created":"2024-08-11","cited_by_count":3,"area":null},{"id":"2506.07863","title":"VIVAT: Virtuous Improving VAE Training through Artifact Mitigation","created":"2025-06-09","cited_by_count":3,"area":null},{"id":"2112.09051","title":"Simultaneous Multivariate Forecast of Space Weather Indices using Deep Neural Network Ensembles","created":"2021-12-16","cited_by_count":2,"area":null},{"id":"2210.13390","title":"On the failure of variational score matching for VAE models","created":"2022-10-24","cited_by_count":2,"area":null},{"id":"2306.08230","title":"Unbiased Learning of Deep Generative Models with Structured Discrete Representations","created":"2023-06-14","cited_by_count":2,"area":null},{"id":"2306.09035","title":"Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings","created":"2023-06-15","cited_by_count":2,"area":null},{"id":"2311.08149","title":"Modeling Complex Disease Trajectories using Deep Generative Models with Semi-Supervised Latent Processes","created":"2023-11-14","cited_by_count":2,"area":null},{"id":"2403.15476","title":"Learning to Infer Generative Template Programs for Visual Concepts","created":"2024-03-20","cited_by_count":2,"area":null},{"id":"2506.23914","title":"Learning robust parameter inference and density reconstruction in flyer plate impact experiments","created":"2025-06-30","cited_by_count":2,"area":null},{"id":"2507.02619","title":"L-VAE: Variational Auto-Encoder with Learnable Beta for Disentangled Representation","created":"2025-07-03","cited_by_count":2,"area":null},{"id":"2112.09414","title":"Disentangled representations: towards interpretation of sex determination from hip bone","created":"2021-12-17","cited_by_count":1,"area":null},{"id":"2303.13004","title":"Adversarially Contrastive Estimation of Conditional Neural Processes","created":"2023-03-23","cited_by_count":1,"area":null},{"id":"2405.15991","title":"R\\'enyi Neural Processes","created":"2024-05-25","cited_by_count":1,"area":null},{"id":"2408.07219","title":"Causal Effect Estimation using identifiable Variational AutoEncoder with Latent Confounders and Post-Treatment Variables","created":"2024-08-13","cited_by_count":1,"area":null},{"id":"2412.04130","title":"Deep priors for satellite image restoration with accurate uncertainties","created":"2024-12-05","cited_by_count":1,"area":null},{"id":"2502.09591","title":"Censor Dependent Variational Inference","created":"2025-02-13","cited_by_count":1,"area":null},{"id":"2506.01522","title":"Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows","created":"2025-06-02","cited_by_count":1,"area":null},{"id":"2605.22691","title":"Latent Spectroscopy: Posterior Collapse as a Feature","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2605.26006","title":"MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control","created":"2026-05-25","cited_by_count":1,"area":null},{"id":"2205.13061","title":"RENs: Relevance Encoding Networks","created":"2022-05-25","cited_by_count":0,"area":null},{"id":"2310.14659","title":"Predicting Accurate Lagrangian Multipliers for Mixed Integer Linear Programs","created":"2023-10-23","cited_by_count":0,"area":null},{"id":"2402.06808","title":"Explain Variance of Prediction in Variational Time Series Models for Clinical Deterioration Prediction","created":"2024-02-09","cited_by_count":0,"area":null},{"id":"2409.09361","title":"Beta-Sigma VAE: Separating beta and decoder variance in Gaussian variational autoencoder","created":"2024-09-14","cited_by_count":0,"area":null},{"id":"2504.17622","title":"Likelihood-Free Variational Autoencoders","created":"2025-04-24","cited_by_count":0,"area":null},{"id":"2511.08946","title":"Improving Conditional VAE with Non-Volume Preserving transformations","created":"2025-11-12","cited_by_count":0,"area":null},{"id":"2602.10751","title":"Predicting integers from continuous parameters","created":"2026-02-11","cited_by_count":0,"area":null},{"id":"2605.12619","title":"Perceived face similarity reflects inverse-generative and naturalistic discriminative objectives","created":"2026-05-12","cited_by_count":0,"area":null}],"next_cursor":null}