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Found 8 papers, 4 papers with code
Improving Time Series Classification Algorithms Using Octave-Convolutional Layers
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.
Self-supervision for health insurance claims data: a Covid-19 use case
In this work, we modify and apply self-supervision techniques to the domain of medical health insurance claims.
Adversarial Attacks on Multivariate Time Series
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.
Insights into LSTM Fully Convolutional Networks for Time Series Classification
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.
Adversarial Attacks on Time Series
In this paper, we propose utilizing an adversarial transformation network (ATN) on a distilled model to attack various time series classification models.
Pathological Voice Classification Using Mel-Cepstrum Vectors and Support Vector Machine
Vocal disorders have affected several patients all over the world.
Multivariate LSTM-FCNs for Time Series Classification
Over the past decade, multivariate time series classification has received great attention.
Ranked #1 on
Time Series Classification
on CharacterTrajectories
LSTM Fully Convolutional Networks for Time Series Classification
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
