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

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

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Greatest papers with code

Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting

19 Dec 2019google-research/google-research

Multi-horizon forecasting problems often contain a complex mix of inputs -- including static (i. e. time-invariant) covariates, known future inputs, and other exogenous time series that are only observed historically -- without any prior information on how they interact with the target.

INTERPRETABLE MACHINE LEARNING TIME SERIES TIME SERIES FORECASTING

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 QUESTION GENERATION 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 FEATURE SELECTION TIME SERIES TIME SERIES CLASSIFICATION

Stock Price Prediction via Discovering Multi-Frequency Trading Patterns

13 Aug 2017microsoft/qlib

Then the future stock prices are predicted as a nonlinear mapping of the combination of these components in an Inverse Fourier Transform (IFT) fashion.

STOCK PRICE PREDICTION TIME SERIES

sktime: A Unified Interface for Machine Learning with Time Series

17 Sep 2019alan-turing-institute/sktime

We present sktime -- a new scikit-learn compatible Python library with a unified interface for machine learning with time series.

TIME SERIES TIME SERIES ANALYSIS TIME SERIES CLASSIFICATION TIME SERIES FORECASTING

Applications of Deep Neural Networks

11 Sep 2020jeffheaton/t81_558_deep_learning

Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output.

TIME SERIES

Adversarial Robustness Toolbox v1.0.0

3 Jul 2018IBM/adversarial-robustness-toolbox

Defending Machine Learning models involves certifying and verifying model robustness and model hardening with approaches such as pre-processing inputs, augmenting training data with adversarial samples, and leveraging runtime detection methods to flag any inputs that might have been modified by an adversary.

GAUSSIAN PROCESSES TIME SERIES

GluonTS: Probabilistic Time Series Models in Python

12 Jun 2019awslabs/gluon-ts

We introduce Gluon Time Series (GluonTS, available at https://gluon-ts. mxnet. io), a library for deep-learning-based time series modeling.

ANOMALY DETECTION TIME SERIES TIME SERIES FORECASTING TIME SERIES PREDICTION

Efficient Matrix Profile Computation Using Different Distance Functions

17 Jan 2019TDAmeritrade/stumpy

The results also show that the ACAMP algorithm is significantly faster than SCRIMP++ (the state of the art matrix profile algorithm) for the case of z-normalized Euclidean distance.

TIME SERIES

Benchmarking time series classification -- Functional data vs machine learning approaches

18 Nov 2019mlr-org/mlr

In order to assess the methods and implementations, we run a benchmark on a wide variety of representative (time series) data sets, with in-depth analysis of empirical results, and strive to provide a reference ranking for which method(s) to use for non-expert practitioners.

TIME SERIES TIME SERIES CLASSIFICATION