Dynamic Time Warping

114 papers with code • 0 benchmarks • 0 datasets

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Use these libraries to find Dynamic Time Warping models and implementations

Most implemented papers

Soft-DTW: a Differentiable Loss Function for Time-Series

mblondel/soft-dtw ICML 2017

We propose in this paper a differentiable learning loss between time series, building upon the celebrated dynamic time warping (DTW) discrepancy.

Learning the Beauty in Songs: Neural Singing Voice Beautifier

moonintheriver/neuralsvb ACL 2022

Furthermore, we propose a latent-mapping algorithm in the latent space to convert the amateur vocal tone to the professional one.

Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models

vincent-leguen/STDL NeurIPS 2019

We introduce a differentiable loss function suitable for training deep neural nets, and provide a custom back-prop implementation for speeding up optimization.

Bake off redux: a review and experimental evaluation of recent time series classification algorithms

aeon-toolkit/aeon 25 Apr 2023

We introduce 30 classification datasets either recently donated to the archive or reformatted to the TSC format, and use these to further evaluate the best performing algorithm from each category.

A user-driven case-based reasoning tool for infilling missing values in daily mean river flow records

erin-list/gapit Environmental Modelling & Software 2006

In this work, we introduce gapIt, a user-driven case-based reasoning tool for infilling gaps in daily mean river flow records.

Multi-Scale Convolutional Neural Networks for Time Series Classification

zdcuob/Fully-Convlutional-Neural-Networks-for-state-of-the-art-time-series-classification- 22 Mar 2016

These methods are ad-hoc and separate the feature extraction part with the classification part, which limits their accuracy performance.

shapeDTW: shape Dynamic Time Warping

jiapingz/shapeDTW 6 Jun 2016

Dynamic Time Warping (DTW) is an algorithm to align temporal sequences with possible local non-linear distortions, and has been widely applied to audio, video and graphics data alignments.

Times series averaging and denoising from a probabilistic perspective on time-elastic kernels

pfmarteau/eKATS 28 Nov 2016

In the light of regularized dynamic time warping kernels, this paper re-considers the concept of time elastic centroid for a setof time series.

TimeNet: Pre-trained deep recurrent neural network for time series classification

kirarenctaon/timenet 23 Jun 2017

Inspired by the tremendous success of deep Convolutional Neural Networks as generic feature extractors for images, we propose TimeNet: a deep recurrent neural network (RNN) trained on diverse time series in an unsupervised manner using sequence to sequence (seq2seq) models to extract features from time series.

Human Motion Analysis with Deep Metric Learning

xrenaa/Human-Motion-Analysis-with-Deep-Metric-Learning ECCV 2018

Nevertheless, we believe that traditional approaches such as L2 distance or Dynamic Time Warping based on hand-crafted local pose metrics fail to appropriately capture the semantic relationship across motions and, as such, are not suitable for being employed as metrics within these tasks.