88 citations · 380 across the 50 of their papers we have counts for
6 papers · 2 filters
Finding Algebraic Structure of Care in Time: A Deep Learning Approach
Phuoc Nguyen, Truyen Tran, Svetha Venkatesh
Understanding the latent processes from Electronic Medical Records could be a game changer in modern healthcare. However, the processes are complex due to the interaction between a…
Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization
Tu Dinh Nguyen, Truyen Tran, Dinh Phung +1
The success of any machine learning system depends critically on effective representations of data. In many cases, it is desirable that a representation scheme uncovers the parts-b…
Statistical Latent Space Approach for Mixed Data Modelling and Applications
Tu Dinh Nguyen, Truyen Tran, Dinh Phung +1
The analysis of mixed data has been raising challenges in statistics and machine learning. One of two most prominent challenges is to develop new statistical techniques and methodo…
Graph Classification via Deep Learning with Virtual Nodes
Trang Pham, Truyen Tran, Hoa Dam +1
Learning representation for graph classification turns a variable-size graph into a fixed-size vector (or matrix). Such a representation works nicely with algebraic manipulations.…
Deep Learning to Attend to Risk in ICU
Phuoc Nguyen, Truyen Tran, Svetha Venkatesh
Modeling physiological time-series in ICU is of high clinical importance. However, data collected within ICU are irregular in time and often contain missing measurements. Since abs…
Learning Deep Matrix Representations
Kien Do, Truyen Tran, Svetha Venkatesh
We present a new distributed representation in deep neural nets wherein the information is represented in native form as a matrix. This differs from current neural architectures th…