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Time Series

211 papers with code · Time Series

Time series deals with sequential data where the data is indexed (ordered) by a time dimension.

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Greatest papers with code

Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models

7 Oct 2016pytorch/fairseq

We observe that our method consistently outperforms BS and previously proposed techniques for diverse decoding from neural sequence models.

IMAGE CAPTIONING MACHINE TRANSLATION TEXT GENERATION TIME SERIES

Distributed and parallel time series feature extraction for industrial big data applications

25 Oct 2016blue-yonder/tsfresh

This problem is especially hard to solve for time series classification and regression in industrial applications such as predictive maintenance or production line optimization, for which each label or regression target is associated with several time series and meta-information simultaneously.

FEATURE IMPORTANCE TIME SERIES TIME SERIES CLASSIFICATION

Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark

12 Oct 2015numenta/NAB

Here we propose the Numenta Anomaly Benchmark (NAB), which attempts to provide a controlled and repeatable environment of open-source tools to test and measure anomaly detection algorithms on streaming data.

ANOMALY DETECTION TIME SERIES

Adversarial Robustness Toolbox v0.4.0

3 Jul 2018IBM/adversarial-robustness-toolbox

The Adversarial Robustness Toolbox (ART) is a Python library designed to support researchers and developers in creating novel defence techniques, as well as in deploying practical defences of real-world AI systems.

TIME SERIES

FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network

NeurIPS 2018 Microsoft/EdgeML

FastRNN addresses these limitations by adding a residual connection that does not constrain the range of the singular values explicitly and has only two extra scalar parameters.

ACTION CLASSIFICATION LANGUAGE MODELLING SPEECH RECOGNITION TIME SERIES TIME SERIES CLASSIFICATION

Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices

NeurIPS 2018 Microsoft/EdgeML

We propose a method, EMI-RNN, that exploits these observations by using a multiple instance learning formulation along with an early prediction technique to learn a model that achieves better accuracy compared to baseline models, while simultaneously reducing computation by a large fraction.

MULTIPLE INSTANCE LEARNING TIME SERIES TIME SERIES CLASSIFICATION

Real numbers, data science and chaos: How to fit any dataset with a single parameter

28 Apr 2019Ranlot/single-parameter-fit

We show how any dataset of any modality (time-series, images, sound...) can be approximated by a well-behaved (continuous, differentiable...) scalar function with a single real-valued parameter.

TIME SERIES

LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

1 Jul 2016chickenbestlover/RNN-Time-series-Anomaly-Detection

Mechanical devices such as engines, vehicles, aircrafts, etc., are typically instrumented with numerous sensors to capture the behavior and health of the machine.

ANOMALY DETECTION TIME SERIES

SOM-VAE: Interpretable Discrete Representation Learning on Time Series

ICLR 2019 JustGlowing/minisom

We evaluate our model in terms of clustering performance and interpretability on static (Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST images, a chaotic Lorenz attractor system with two macro states, as well as on a challenging real world medical time series application on the eICU data set.

DIMENSIONALITY REDUCTION REPRESENTATION LEARNING TIME SERIES

Detection of Structural Change in Geographic Regions of Interest by Self Organized Mapping: Las Vegas City and Lake Mead across the Years

29 Mar 2018JustGlowing/minisom

Time-series of satellite images may reveal important data about changes in environmental conditions and natural or urban landscape structures that are of potential interest to citizens, historians, or policymakers.

QUANTIZATION TIME SERIES