research
∙
09/20/2022
Learning Sparse Latent Representations for Generator Model
Sparsity is a desirable attribute. It can lead to more efficient and mor...
share
research
∙
09/19/2022
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model
This paper studies the fundamental problem of learning energy-based mode...
research
∙
07/29/2022
A Modified Union Bound on Symbol Error Probability for Fading Channels
In this paper, we propose a new upper bound on the error probability per...
research
∙
12/09/2021
Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs
With the wide application of electronic health records (EHR) in healthca...
research
∙
07/30/2021
Combined Radar and Communications with Phase-Modulated Frequency Permutations
This paper focuses on the combined radar and communications problem and ...
research
∙
05/24/2021
Frequency Permutations for Joint Radar and Communications
This paper presents a new joint radar and communication technique based ...
research
∙
06/15/2020
Learning Latent Space Energy-Based Prior Model
The generator model assumes that the observed example is generated by a ...
research
∙
06/10/2020
Joint Training of Variational Auto-Encoder and Latent Energy-Based Model
This paper proposes a joint training method to learn both the variationa...
research
∙
12/04/2019
Learning Deep Generative Models with Short Run Inference Dynamics
This paper studies the fundamental problem of learning deep generative m...
research
∙
11/19/2019
Deep Unsupervised Clustering with Clustered Generator Model
This paper addresses the problem of unsupervised clustering which remain...
research
∙
03/29/2019
On the Anatomy of MCMC-based Maximum Likelihood Learning of Energy-Based Models
This study investigates the effects Markov Chain Monte Carlo (MCMC) samp...
research
∙
12/28/2018
Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model
This paper proposes the divergence triangle as a framework for joint tra...
research
∙
10/09/2018
A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models
The pattern theory of Grenander is a mathematical framework where the pa...
research
∙
06/16/2018
Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry
We propose a deformable generator model to disentangle the appearance an...
research
∙
05/14/2018
Replicating Active Appearance Model by Generator Network
A recent Cell paper [Chang and Tsao, 2017] reports an interesting discov...
research
∙
06/28/2016
