Models

Probability Distillation: A Caveat and Alternatives UAI 2019 Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning ICML 2019 ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees ICLR 2019 Progressive Reconstruction of Visual Structure for Image Inpainting ICCV 2019 Provable Gradient Variance Guarantees for Black-Box Variational Inference NeurIPS 2019 PU-GAN: A Point Cloud Upsampling Adversarial Network ICCV 2019 Pun-GAN: Generative Adversarial Network for Pun Generation EMNLP 2019 Pyro: Deep Universal Probabilistic Programming JMLR 2019 Quality Aware Generative Adversarial Networks NeurIPS 2019 Quantity doesn’t buy quality syntax with neural language models EMNLP 2019 Quantum Wasserstein Generative Adversarial Networks NeurIPS 2019 R2GAN: Cross-Modal Recipe Retrieval With Generative Adversarial Network CVPR 2019 Randomized Value Functions via Multiplicative Normalizing Flows UAI 2019 Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning UAI 2019 RankSRGAN: Generative Adversarial Networks With Ranker for Image Super-Resolution ICCV 2019 Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation EMNLP 2019 Realistic Image Generation using Region-phrase Attention ACML 2019 Real-Time Neural Text-to-Speech with Sequence-to-Sequence Acoustic Model and WaveGlow or Single Gaussian WaveRNN Vocoders Interspeech 2019 Recognizing Unseen Attribute-Object Pair with Generative Model AAAI 2019 Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring IJCAI 2019 Recurrent MVSNet for High-Resolution Multi-View Stereo Depth Inference CVPR 2019 Reducing Noise in GAN Training with Variance Reduced Extragradient NeurIPS 2019 Re-examination of the Role of Latent Variables in Sequence Modeling NeurIPS 2019 Re-Identification Supervised Texture Generation CVPR 2019 Relevant and Informative Response Generation using Pointwise Mutual Information ACL 2019