Generative Models

Max-Sliced Wasserstein Distance and Its Use for GANs CVPR 2019 Mixture Density Generative Adversarial Networks CVPR 2019 Neural Linguistic Steganography EMNLP 2019 Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses NeurIPS 2019 PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network AAAI 2019 Practical Full Resolution Learned Lossless Image Compression CVPR 2019 Tensor Monte Carlo: Particle Methods for the GPU era NeurIPS 2019 The Implicit Metropolis-Hastings Algorithm NeurIPS 2019 Banach Wasserstein GAN NeurIPS 2018 Constrained Graph Variational Autoencoders for Molecule Design NeurIPS 2018 Multivariate Time Series Imputation with Generative Adversarial Networks NeurIPS 2018 Causal Effect Inference with Deep Latent-Variable Models NeurIPS 2017 Filtering Variational Objectives NeurIPS 2017 Inferring Generative Model Structure with Static Analysis NeurIPS 2017 On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models NeurIPS 2017 Population Matching Discrepancy and Applications in Deep Learning NeurIPS 2017 Wasserstein Learning of Deep Generative Point Process Models NeurIPS 2017 f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization NeurIPS 2016 On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification PGM 2016 Regularizing Max-Margin Exemplars by Reconstruction and Generative Models CVPR 2015 A Generative Model for Parts-based Object Segmentation NeurIPS 2012 Unsupervised Structure Discovery for Semantic Analysis of Audio NeurIPS 2012 Free energy score space NeurIPS 2009 Evaluating probabilities under high-dimensional latent variable models NeurIPS 2008 Generative versus discriminative training of RBMs for classification of fMRI images NeurIPS 2008