10708 Probabilistic Graphical Models

Completed Student Projects

#	Project	Report
1	Predicting the precense of industrial odors using crowdsourced and air quality monitoring data. Yen-Chia Hsu	report
2	Don't Fall for Dropouts: Bayesian Learning on Single-cell RNA-seq Data. Zongge Liu, Yifeng Tao, Lingxue Zhu	report
3	A-EPSGLD: An Asynchronous Distributed Framework for Efficient Large-scale LDA Inference. Yuan Yang, Yifan Yang, Min Hun Lee	report
4	Automatic Coloring Using Factor Graph. Yuan Liu, Fan Jiang, Yangyi Lu	report
5	Spatiotemporal Dynamics of Neural Signals: Modeling and Inference. Yuanning Li	report
6	Prediction in Nonstationary Environment by Making Use of Causal Knowledge. Biwei Huang	report
7	Sequence Generation and Classification with VAEs and RNNs. Jay Hennig, Akash Umakantha, Ryan Williamson	report, demo
8	Phased-LSTM Based Predictive Model for longitudinal EHR Data with Missing Values. Seo-Jin Bang, Yuchuan Wang, Yang Yang	report
9	Compositional Reasoning for Visual Question Answering. Jayanth Koushik, Hiroaki Hayashi, Devendra Singh Sachan	report
10	Probabilistic Interpretations of Recurrent Neural Networks. Yo Joong Choe, Jaehyeok Shin, Neil Spencer	report
11	Wasserstein Training of Deep Boltzmann Machines. Chaoyang Wang, Tian Tong, Yang Zou	report
12	Variational Neural Conversational Model. Xupeng Tong, Yikang Li, Chao-Ming Yen	report
13	Combining LSTM and Latent Topic Modeling for Mortality Prediction. Yohan Jo, Lisa Lee, Shruti Palaskar	report
14	Unsupervised Compositor Attribution in Historical Documents. Maria Ryskina	report
15	Deep Modeling of Longitudinal Medical Data. Baoyu Jing, Huiting Liu, Mingxing Liu	report
16	Good Semi-supervised Learning That Requires a Bad GAN. Zihang Dai, Fan Yang, Zhilin Yang	report, arXiv