density estimation

Flows for simultaneous manifold learning and density estimation NeurIPS 2020 From Variational to Deterministic Autoencoders ICLR 2020 Gaussian Gated Linear Networks NeurIPS 2020 Gaussianization Flows AISTATS 2020 Generative Flows with Matrix Exponential ICML 2020 Gradient Boosted Normalizing Flows NeurIPS 2020 HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting CVPR 2020 Kernel Conditional Density Operators AISTATS 2020 Learning from Positive and Unlabeled Data without Explicit Estimation of Class Prior AAAI 2020 Learning Weighted Model Integration Distributions AAAI 2020 Local Differential Privacy for Sampling AISTATS 2020 Locally Masked Convolution for Autoregressive Models UAI 2020 Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows NeurIPS 2020 Modeling Noisy Annotations for Crowd Counting NeurIPS 2020 NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity NeurIPS 2020 Neural Likelihoods via Cumulative Distribution Functions UAI 2020 Nonparametric Fisher Geometry with Application to Density Estimation UAI 2020 Non-parametric Models for Non-negative Functions NeurIPS 2020 Normalizing Flows With Multi-Scale Autoregressive Priors CVPR 2020 On the Discrepancy between Density Estimation and Sequence Generation EMNLP 2020 Relative gradient optimization of the Jacobian term in unsupervised deep learning NeurIPS 2020 Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows ICML 2020 Residual Sum-Product Networks PGM 2020 Reverse Perspective Network for Perspective-Aware Object Counting CVPR 2020 Robust Density Estimation under Besov IPM Losses NeurIPS 2020