activity
20182021
most citedInsights into LSTM Fully Convolutional Networks for Time Series Classification

212 citations · 221 across the 6 of their papers we have counts for

collaborators

10 papers

cs.LG2021

Improving Time Series Classification Algorithms Using Octave-Convolutional Layers

Samuel Harford, Fazle Karim, Houshang Darabi

Deep learning models utilizing convolution layers have achieved state-of-the-art performance on univariate time series classification tasks. In this work, we propose improving CNN…

cs.LG2021

Process Mining Model to Predict Mortality in Paralytic Ileus Patients

Maryam Pishgar, Martha Razo, Julian Theis +1

Paralytic Ileus (PI) patients are at high risk of death when admitted to the Intensive care unit (ICU), with mortality as high as 40\%. There is minimal research concerning PI pati…

cs.LG2020

Adversarial Attacks on Multivariate Time Series

Samuel Harford, Fazle Karim, Houshang Darabi

Classification models for the multivariate time series have gained significant importance in the research community, but not much research has been done on generating adversarial s…

cs.AI2020

Adversarial System Variant Approximation to Quantify Process Model Generalization

Julian Theis, Houshang Darabi

In process mining, process models are extracted from event logs using process discovery algorithms and are commonly assessed using multiple quality dimensions. While the metrics th…

cs.LG2019

A Computer-Aided System for Determining the Application Range of a Warfarin Clinical Dosing Algorithm Using Support Vector Machines with a Polynomial Kernel Function

Ashkan Sharabiani, Adam Bress, William Galanter +2

Determining the optimal initial dose for warfarin is a critically important task. Several factors have an impact on the therapeutic dose for individual patients, such as patients'…

cs.LG2019

Decay Replay Mining to Predict Next Process Events

Julian Theis, Houshang Darabi

In complex processes, various events can happen in different sequences. The prediction of the next event given an a-priori process state is of importance in such processes. Recent…