density estimation

Red PANDA: Disambiguating Image Anomaly Detection by Removing Nuisance Factors ICLR 2023 SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection NeurIPS 2023 Spherical Sliced-Wasserstein ICLR 2023 Spread Flows for Manifold Modelling AISTATS 2023 Squared Neural Families: A New Class of Tractable Density Models NeurIPS 2023 Structured Neural Networks for Density Estimation and Causal Inference NeurIPS 2023 Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures COLT 2023 Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning CoRL 2023 Training Normalizing Flows from Dependent Data ICML 2023 What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization NeurIPS 2023 Your Diffusion Model is Secretly a Zero-Shot Classifier ICCV 2023 k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension NeurIPS 2022 AdaCat: Adaptive categorical discretization for autoregressive models UAI 2022 Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals AISTATS 2022 An Improper Estimator with Optimal Excess Risk in Misspecified Density Estimation and Logistic Regression JMLR 2022 AUTM flow: atomic unrestricted time machine for monotonic normalizing flows UAI 2022 Autoregressive Quantile Flows for Predictive Uncertainty Estimation ICLR 2022 Beyond black box densities: Parameter learning for the deviated components NeurIPS 2022 ButterflyFlow: Building Invertible Layers with Butterfly Matrices ICML 2022 C*-algebra Net: A New Approach Generalizing Neural Network Parameters to C*-algebra ICML 2022 Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation ICML 2022 Concrete Score Matching: Generalized Score Matching for Discrete Data NeurIPS 2022 Conditionally Tractable Density Estimation using Neural Networks AISTATS 2022 Dataset Inference for Self-Supervised Models NeurIPS 2022 Density-driven Regularization for Out-of-distribution Detection NeurIPS 2022