48 citations · 144 across the 28 of their papers we have counts for
7 papers · 1 filter
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model
Zhisheng Xiao, Tian Han
This paper studies the fundamental problem of learning energy-based model (EBM) in the latent space of the generator model. Learning such prior model typically requires running cos…
Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs
Chang Lu, Tian Han, Yue Ning
With the wide application of electronic health records (EHR) in healthcare facilities, health event prediction with deep learning has gained more and more attention. A common featu…
Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI
Quanshi Zhang, Tian Han, Lixin Fan +5
This is the Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI. Deep neural networks (DNNs) have undoubtedly brought grea…
Generative Text Modeling through Short Run Inference
Bo Pang, Erik Nijkamp, Tian Han +1
Latent variable models for text, when trained successfully, accurately model the data distribution and capture global semantic and syntactic features of sentences. The prominent ap…
Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling
Bo Pang, Erik Nijkamp, Jiali Cui +2
This paper proposes a latent space energy-based prior model for semi-supervised learning. The model stands on a generator network that maps a latent vector to the observed example.…
Learning Latent Space Energy-Based Prior Model for Molecule Generation
Bo Pang, Tian Han, Ying Nian Wu
Deep generative models have recently been applied to molecule design. If the molecules are encoded in linear SMILES strings, modeling becomes convenient. However, models relying on…
Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry
Xianglei Xing, Ruiqi Gao, Tian Han +2
We present a deformable generator model to disentangle the appearance and geometric information for both image and video data in a purely unsupervised manner. The appearance genera…