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

212 citations · 212 across the 4 of their papers we have counts for

collaborators

6 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.CL2021

Self-supervision for health insurance claims data: a Covid-19 use case

Emilia Apostolova, Fazle Karim, Guido Muscioni +2

In this work, we modify and apply self-supervision techniques to the domain of medical health insurance claims. We model patients' healthcare claims history analogous to free-text…

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.LG2019

Adversarial Attacks on Time Series

Fazle Karim, Somshubra Majumdar, Houshang Darabi

Time series classification models have been garnering significant importance in the research community. However, not much research has been done on generating adversarial samples f…

cs.LG2019212 cited

Insights into LSTM Fully Convolutional Networks for Time Series Classification

Fazle Karim, Somshubra Majumdar, Houshang Darabi

Long Short Term Memory Fully Convolutional Neural Networks (LSTM-FCN) and Attention LSTM-FCN (ALSTM-FCN) have shown to achieve state-of-the-art performance on the task of classifyi…

eess.AS2018

Pathological Voice Classification Using Mel-Cepstrum Vectors and Support Vector Machine

Maryam Pishgar, Fazle Karim, Somshubra Majumdar +1

Vocal disorders have affected several patients all over the world. Due to the inherent difficulty of diagnosing vocal disorders without sophisticated equipment and trained personne…