Yunchen Pu
12 papers · 2016–2019 · 8 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+4 more ↓ Show less ↑
🗺️ Taxonomy Completionist (38) 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🧭 Keyword Pioneer
📈
Trend Setter
🚀
Conference Pioneer
💎
Century Club · Bronze
🗃️
Keyword Collector
(73)
Top co-authors
Research topics
Machine Learning
(11)
Deep Learning
(9)
Core Methods
(6)
Models
(6)
Computer Vision
(5)
Architectures
(5)
Learning Types · Machine Learning
(5)
Learning Types · Deep Learning
(4)
Optimization & Theory
(4)
Artificial Intelligence
(3)
Bayesian & Probabilistic · Machine Learning
(3)
Generation · Computer Vision
(3)
Natural Language Processing
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Generation · Natural Language Processing
(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
Continuous-Time Flows for Efficient Inference and Density Estimation
ICML 2018
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
ICML 2018
Symmetric Variational Autoencoder and Connections to Adversarial Learning
AISTATS 2018
Learning Generic Sentence Representations Using Convolutional Neural Networks
EMNLP 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling
ACL 2017
Semantic Compositional Networks for Visual Captioning
CVPR 2017
Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis
AISTATS 2017
A Deep Generative Deconvolutional Image Model
AISTATS 2016
Learning Weight Uncertainty With Stochastic Gradient MCMC for Shape Classification
CVPR 2016
Variational Autoencoder for Deep Learning of Images, Labels and Captions
NeurIPS 2016