{"total":22,"rows":[{"id":"2206.07769","title":"HyperImpute: Generalized Iterative Imputation with Automatic Model Selection","created":"2022-06-15","cited_by_count":83,"area":null},{"id":"2204.07172","title":"Diagnosing and Fixing Manifold Overfitting in Deep Generative Models","created":"2022-04-14","cited_by_count":28,"area":null},{"id":"2302.11756","title":"Learning Manifold Dimensions with Conditional Variational Autoencoders","created":"2023-02-23","cited_by_count":20,"area":null},{"id":"2206.15078","title":"Laplacian Autoencoders for Learning Stochastic Representations","created":"2022-06-30","cited_by_count":10,"area":null},{"id":"2306.08984","title":"Tree Variational Autoencoders","created":"2023-06-15","cited_by_count":10,"area":null},{"id":"2206.09453","title":"Bounding Evidence and Estimating Log-Likelihood in VAE","created":"2022-06-19","cited_by_count":6,"area":null},{"id":"2109.09374","title":"Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection","created":"2021-09-20","cited_by_count":4,"area":null},{"id":"2205.09546","title":"Deterministic training of generative autoencoders using invertible layers","created":"2022-05-19","cited_by_count":4,"area":null},{"id":"2106.02390","title":"Online reinforcement learning with sparse rewards through an active inference capsule","created":"2021-06-04","cited_by_count":3,"area":null},{"id":"2201.05890","title":"Robust uncertainty estimates with out-of-distribution pseudo-inputs training","created":"2022-01-15","cited_by_count":3,"area":null},{"id":"2209.15321","title":"Leveraging variational autoencoders for multiple data imputation","created":"2022-09-30","cited_by_count":3,"area":null},{"id":"2407.15161","title":"FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference","created":"2024-07-21","cited_by_count":3,"area":null},{"id":"2308.09078","title":"Conditional Sampling of Variational Autoencoders via Iterated Approximate Ancestral Sampling","created":"2023-08-17","cited_by_count":2,"area":null},{"id":"2403.03069","title":"Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families","created":"2024-03-05","cited_by_count":2,"area":null},{"id":"2107.12329","title":"AASAE: Augmentation-Augmented Stochastic Autoencoders","created":"2021-07-26","cited_by_count":1,"area":null},{"id":"2202.12707","title":"Benchmarking Generative Latent Variable Models for Speech","created":"2022-02-22","cited_by_count":1,"area":null},{"id":"2204.10400","title":"Interpolation of Missing Swaption Volatility Data using Gibbs Sampling on Variational Autoencoders","created":"2022-04-21","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":"2205.10347","title":"Diverse super-resolution with pretrained deep hiererarchical VAEs","created":"2022-05-20","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":"2411.05998","title":"Filling in Missing FX Implied Volatilities with Uncertainties: Improving VAE-Based Volatility Imputation","created":"2024-11-08","cited_by_count":0,"area":null},{"id":"2601.18676","title":"Quasi Monte Carlo methods enable extremely low-dimensional deep generative models","created":"2026-01-26","cited_by_count":0,"area":null}],"next_cursor":null}