Generative Models

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization AAAI 2021 Modified Frank Wolfe in Probability Space NeurIPS 2021 Moser Flow: Divergence-based Generative Modeling on Manifolds NeurIPS 2021 Partition-Guided GANs CVPR 2021 Sketch2Model: View-Aware 3D Modeling From Single Free-Hand Sketches CVPR 2021 Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows NeurIPS 2021 Transductive Zero-Shot Learning by Decoupled Feature Generation WACV 2021 Conditional Generative Neural Decoding with Structured CNN Feature Prediction AAAI 2020 Conditional Neural Generation using Sub-Aspect Functions for Extractive News Summarization EMNLP 2020 COT-GAN: Generating Sequential Data via Causal Optimal Transport NeurIPS 2020 Decision-Making with Auto-Encoding Variational Bayes NeurIPS 2020 Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity NeurIPS 2020 Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder ACL 2020 Generating Realistic Stock Market Order Streams AAAI 2020 Gradient Estimation with Stochastic Softmax Tricks NeurIPS 2020 Introducing Probabilistic Bézier Curves for N-Step Sequence Prediction AAAI 2020 Joint Training of Variational Auto-Encoder and Latent Energy-Based Model CVPR 2020 McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020 Meeting the 2020 Duolingo Challenge on a Shoestring ACL 2020 Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation NeurIPS 2020 StructEdit: Learning Structural Shape Variations CVPR 2020 A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation NeurIPS 2019 G2SAT: Learning to Generate SAT Formulas NeurIPS 2019 Generalized Sliced Wasserstein Distances NeurIPS 2019 Learning Mixtures of Plackett-Luce Models from Structured Partial Orders NeurIPS 2019