16 citations · 39 across the 10 of their papers we have counts for
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stat.ML2019
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference
Erik Nijkamp, Bo Pang, Tian Han +3
This paper studies the fundamental problem of learning deep generative models that consist of multiple layers of latent variables organized in top-down architectures. Such models h…
stat.ML2019★ 1 cited
Deep Unsupervised Clustering with Clustered Generator Model
Dandan Zhu, Tian Han, Linqi Zhou +2
This paper addresses the problem of unsupervised clustering which remains one of the most fundamental challenges in machine learning and artificial intelligence. We propose the clu…
stat.ML2019★ 5 cited
Neural Architecture Search for Joint Optimization of Predictive Power and Biological Knowledge
Zijun Zhang, Linqi Zhou, Liangke Gou +1
We report a neural architecture search framework, BioNAS, that is tailored for biomedical researchers to easily build, evaluate, and uncover novel knowledge from interpretable deep…