Density Estimation

Approximate Kernel Density Estimation under Metric-based Local Differential Privacy UAI 2024 Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization ICLR 2024 Learning from Sparse Offline Datasets via Conservative Density Estimation ICLR 2024 Lifting Architectural Constraints of Injective Flows ICLR 2024 Spatial properties of Bayesian unsupervised trees COLT 2024 Subtractive Mixture Models via Squaring: Representation and Learning ICLR 2024 Adaptive Riemannian stochastic gradient descent and reparameterization for Gaussian mixture model fitting ACML 2023 Beyond Parallel Pancakes: Quasi-Polynomial Time Guarantees for Non-Spherical Gaussian Mixtures COLT 2023 Convergence Rates of a Class of Multivariate Density Estimation Methods Based on Adaptive Partitioning JMLR 2023 Pitfalls of Gaussians as a noise distribution in NCE ICLR 2023 SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians COLT 2023 Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures COLT 2023 Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound PGM 2022 Entropy Estimation via Normalizing Flow AAAI 2022 On the Role of Channel Capacity in Learning Gaussian Mixture Models COLT 2022 Private and polynomial time algorithms for learning Gaussians and beyond COLT 2022 A Statistical Perspective on Coreset Density Estimation AISTATS 2021 A Statistical Taylor Theorem and Extrapolation of Truncated Densities COLT 2021 Sequential prediction under log-loss and misspecification COLT 2021 Set Prediction without Imposing Structure as Conditional Density Estimation ICLR 2021 Sinusoidal Flow: A Fast Invertible Autoregressive Flow ACML 2021 Bessel Smoothing and Multi-Distribution Property Estimation COLT 2020 Locally Private Hypothesis Selection COLT 2020 On the Discrepancy between Density Estimation and Sequence Generation EMNLP 2020 Residual Sum-Product Networks PGM 2020