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Generative Models

6381 directly classified papers

Papers per year

Papers

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models NIPS 2020
Low Distortion Block-Resampling with Spatially Stochastic Networks NIPS 2020
Telescoping Density-Ratio Estimation NIPS 2020
Gradient Estimation with Stochastic Softmax Tricks NIPS 2020
Woodbury Transformations for Deep Generative Flows NIPS 2020
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence NIPS 2020
Wavelet Flow: Fast Training of High Resolution Normalizing Flows NIPS 2020
Bootstrapping neural processes NIPS 2020
BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images NIPS 2020
Denoising Diffusion Probabilistic Models NIPS 2020
Barking up the right tree: an approach to search over molecule synthesis DAGs NIPS 2020
Swapping Autoencoder for Deep Image Manipulation NIPS 2020
Generating Correct Answers for Progressive Matrices Intelligence Tests NIPS 2020
Implicit Neural Representations with Periodic Activation Functions NIPS 2020
Multi-Fidelity Bayesian Optimization via Deep Neural Networks NIPS 2020
Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation NIPS 2020
COT-GAN: Generating Sequential Data via Causal Optimal Transport NIPS 2020
Further Analysis of Outlier Detection with Deep Generative Models NIPS 2020
Constraining Variational Inference with Geometric Jensen-Shannon Divergence NIPS 2020
Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control NIPS 2020
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets NIPS 2020
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data NIPS 2020
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining NIPS 2020
Training Generative Adversarial Networks with Limited Data NIPS 2020
Improved Techniques for Training Score-Based Generative Models NIPS 2020