← Authors

Yunchen Pu

12 papers · 2016–2019 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) 🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (40) 🌱 Topic Pioneer πŸ’Ž Century Club (12) πŸ—ƒοΈ Keyword Collector (73) πŸš€ Conference Pioneer

Conferences

AISTATS (3) CVPR (2) ICML (2) AAAI (1) ACL (1) EMNLP (1) ICCV (1) NIPS (1)

Top co-authors

Lawrence Carin (9) Chunyuan Li (8) Zhe Gan (6) Changyou Chen (5) Ricardo Henao (4) Andrew Stevens (4) Qinliang Su (2) Shuyang Dai (2) Liqun Chen (2) Xiaodong He (2)

Keywords

convolutional neural network (3) generative model (2) dictionary learning (2) adversarial learning (2) image classification (2) image generation (2) weight uncertainty (2) variational autoencoder (2) stochastic gradient markov chain monte carlo (2) stochastic gradient mcmc (2) recurrent neural network (2) long short-term memory (2) language modeling (1) video captioning (1) density estimation (1) compressive sensing (1) semi-supervised learning (1) bayesian inference (1) posterior sampling (1) bayesian learning (1)

Papers

Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019
l-Net: Reconstruct Hyperspectral Images From a Snapshot Measurement ICCV 2019
Symmetric Variational Autoencoder and Connections to Adversarial Learning AISTATS 2018
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets ICML 2018
Continuous-Time Flows for Efficient Inference and Density Estimation ICML 2018
Learning Generic Sentence Representations Using Convolutional Neural Networks EMNLP 2017
Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis AISTATS 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling ACL 2017
Semantic Compositional Networks for Visual Captioning CVPR 2017
Learning Weight Uncertainty With Stochastic Gradient MCMC for Shape Classification CVPR 2016
A Deep Generative Deconvolutional Image Model AISTATS 2016
Variational Autoencoder for Deep Learning of Images, Labels and Captions NIPS 2016