Generative Model

How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules ICLR 2023 Language Models are Realistic Tabular Data Generators ICLR 2023 ProtoDiffusion: Classifier-Free Diffusion Guidance with Prototype Learning ACML 2023 Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders ICLR 2023 VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation NeurIPS 2023 Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps ICLR 2022 Denoising Likelihood Score Matching for Conditional Score-based Data Generation ICLR 2022 Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization NeurIPS 2022 Self-Consistency of the Fokker Planck Equation COLT 2022 Tackling the Generative Learning Trilemma with Denoising Diffusion GANs ICLR 2022 Disentangled Recurrent Wasserstein Autoencoder ICLR 2021 GAN "Steerability" without optimization ICLR 2021 Generalized Energy Based Models ICLR 2021 Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation EMNLP 2020 On the Encoder-Decoder Incompatibility in Variational Text Modeling and Beyond ACL 2020 Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay IJCAI 2019 Generative Question Answering: Learning to Answer the Whole Question ICLR 2019 Lagging Inference Networks and Posterior Collapse in Variational Autoencoders ICLR 2019 The relativistic discriminator: a key element missing from standard GAN ICLR 2019 Learning Latent Permutations with Gumbel-Sinkhorn Networks ICLR 2018 Sobolev GAN ICLR 2018 The Importance of Generation Order in Language Modeling EMNLP 2018 Conditional Generative Moment-Matching Networks NeurIPS 2016 Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data NeurIPS 2016 Learnable Visual Markers NeurIPS 2016