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

19 September 2019

Papers citing "Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models"

7 / 7 papers shown

Title
An End-to-End Framework for Optimizing Foot Trajectory and Force in Dry Adhesion Legged Wall-Climbing Robots Jichun Xiao Jiawei Nie Lina Hao Zhi Li 21 0 0 28 Apr 2025
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization Xuhai Xu Han Zhang Yasaman S. Sefidgar Yiyi Ren Xin Liu ... Tim Althoff Margaret E. Morris E. Riskin Jennifer Mankoff A. Dey 22 38 0 04 Nov 2022
Latent Time-Adaptive Drift-Diffusion Model Gabriele Cimolino F. Rivest 19 0 0 04 Jun 2021
Time Series Alignment with Global Invariances Titouan Vayer R. Tavenard Laetitia Chapel Nicolas Courty Rémi Flamary Yann Soullard AI4TS 4 16 0 10 Feb 2020
Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories Ian Fox Lynn Ang M. Jaiswal R. Pop-Busui Jenna Wiens OOD AI4TS 54 77 0 14 Jun 2018
Soft-DTW: a Differentiable Loss Function for Time-Series Marco Cuturi Mathieu Blondel AI4TS 127 601 0 05 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015