| Diffeomorphic Temporal Alignment Nets | Ron A Shapira Weber · Matan Eyal · Nicki Skafte · Oren Shriki · Oren Freifeld |
| DTWNet: a Dynamic Time Warping Network | Xingyu Cai · Tingyang Xu · Jinfeng Yi · Junzhou Huang · Sanguthevar Rajasekaran |
| Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting | Shiyang Li · Xiaoyong Jin · Yao Xuan · Xiyou Zhou · Wenhu Chen · Yu-Xiang Wang · Xifeng Yan |
| Fully Neural Network based Model for General Temporal Point Processes | Takahiro Omi · naonori ueda · Kazuyuki Aihara |
| GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series | Edward De Brouwer · Jaak Simm · Adam Arany · Yves Moreau |
| High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes | David Salinas · Michael Bohlke-Schneider · Laurent Callot · Roberto Medico · Jan Gasthaus |
| Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling | Qitian Wu · Zixuan Zhang · Xiaofeng Gao · Junchi Yan · Guihai Chen |
| Learning Representations for Time Series Clustering | Qianli Ma · Jiawei Zheng · Sen Li · Gary W Cottrell |
| Multi-Resolution Weak Supervision for Sequential Data | Paroma Varma · Frederic Sala · Shiori Sagawa · Jason Fries · Daniel Fu · Saelig Khattar · Ashwini Ramamoorthy · Ke Xiao · Kayvon Fatahalian · James Priest · Christopher Ré |
| Neural Jump Stochastic Differential Equations | Junteng Jia · Austin Benson |
| Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models | Vincent LE GUEN · Nicolas THOME |
| Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting | Rajat Sen · Hsiang-Fu Yu · Inderjit S Dhillon |
| Unsupervised Scalable Representation Learning for Multivariate Time Series | Jean-Yves Franceschi · Aymeric Dieuleveut · Martin Jaggi |