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generative modeling

148 papers

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Also known as

IGM

Co-occurring keywords

generative model (2889) diffusion model (3720) optimal transport (945) image generation (2069) normalizing flow (354) variational inference (2069) variational autoencoder (1282) neural network (6616) density estimation (397) energy-based model (248)

Papers

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling NIPS 2019
Unsupervised Primitive Discovery for Improved 3D Generative Modeling CVPR 2019
Learning Flexible Latent Representations via Encapsulated Variational Encoders AAAI 2019
Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets AAAI 2019
Improved Conditional VRNNs for Video Prediction ICCV 2019
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models NIPS 2019
Residual Flows for Invertible Generative Modeling NIPS 2019
Generalized Sliced Wasserstein Distances NIPS 2019
Defending Neural Backdoors via Generative Distribution Modeling NIPS 2019
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions ICML 2019
Learning Independent Causal Mechanisms ICML 2018
Geometrically Coupled Monte Carlo Sampling NIPS 2018
Autoregressive Quantile Networks for Generative Modeling ICML 2018
Estimation of Gap Between Current Language Models and Human Performance INTERSPEECH 2017
Population Matching Discrepancy and Applications in Deep Learning NIPS 2017
What's Wrong With That Object? Identifying Images of Unusual Objects by Modelling the Detection Score Distribution CVPR 2016
Language Identification Based on Generative Modeling of Posteriorgram Sequences Extracted from Frame-by-Frame DNNs and LSTM-RNNs INTERSPEECH 2016
Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Learn Neural Networks JMLR 2016
Accurate and conservative estimates of MRF log-likelihood using reverse annealing AISTATS 2015
Enriching Visual Knowledge Bases via Object Discovery and Segmentation CVPR 2014
Generative Modeling for Maximizing Precision and Recall in Information Visualization AISTATS 2011
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NIPS 2007
Mixture Regression for Covariate Shift NIPS 2006