no code implementations • 28 Sep 2021 • Samuel Harford, Fazle Karim, Houshang Darabi
In this paper, we experimentally show that by substituting convolutions with OctConv, we significantly improve accuracy for time series classification tasks for most of the benchmark datasets.
no code implementations • 3 Aug 2021 • Maryam Pishgar, Martha Razo, Julian Theis, Houshang Darabi
There is a need for more accurate prediction modeling for ICU patients diagnosed with PI.
no code implementations • 1 Aug 2021 • Julian Theis, Houshang Darabi
This paper proposes an approach to further interlock the process model of Decay Replay Mining with its neural network for next event prediction.
no code implementations • 13 Jul 2021 • Julian Theis, Ilia Mokhtarian, Houshang Darabi
"Adversarial System Variant Approximation to Quantify Process Model Generalization."
no code implementations • 31 Mar 2020 • 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 samples for these models.
2 code implementations • 26 Mar 2020 • Julian Theis, Houshang Darabi
Sequence Generative Adversarial Networks are trained on the variants contained in an event log with the intention to approximate the underlying variant distribution of the system behavior.
no code implementations • 21 Mar 2019 • Ashkan Sharabiani, Adam Bress, William Galanter, Rezvan Nazempour, Houshang Darabi
Using a sample of 4, 237 patients, we have proposed a companion classification model to one of the most popular dosing algorithms (International Warfarin Pharmacogenetics Consortium (IWPC) clinical model), which identifies the appropriate cohort of patients for applying this model.
1 code implementation • 12 Mar 2019 • Julian Theis, Houshang Darabi
Recent methods have proposed deep learning techniques such as recurrent neural networks, developed on raw event logs, to predict the next event from a process state.
2 code implementations • 27 Feb 2019 • Fazle Karim, Somshubra Majumdar, Houshang Darabi
In this paper, we propose utilizing an adversarial transformation network (ATN) on a distilled model to attack various time series classification models.
4 code implementations • 27 Feb 2019 • Fazle Karim, Somshubra Majumdar, Houshang Darabi
In this paper, we perform a series of ablation tests (3627 experiments) on LSTM-FCN and ALSTM-FCN to provide a better understanding of the model and each of its sub-module.
no code implementations • 23 Feb 2019 • Julian Theis, Houshang Darabi
Based on users' behavior logs tracked by a Java application suitable for multi-application and multi-instance environments, we demonstrate the applicability for a specific task in a common Windows environment utilizing realistic simulated behaviors of users.
no code implementations • 19 Dec 2018 • Maryam Pishgar, Fazle Karim, Somshubra Majumdar, Houshang Darabi
Vocal disorders have affected several patients all over the world.
7 code implementations • 14 Jan 2018 • Fazle Karim, Somshubra Majumdar, Houshang Darabi, Samuel Harford
Over the past decade, multivariate time series classification has received great attention.
Ranked #1 on Time Series Classification on CharacterTrajectories
9 code implementations • 8 Sep 2017 • Fazle Karim, Somshubra Majumdar, Houshang Darabi, Shun Chen
We propose the augmentation of fully convolutional networks with long short term memory recurrent neural network (LSTM RNN) sub-modules for time series classification.
Ranked #2 on Outlier Detection on ECG5000