Rough Transformers for Continuous and Efficient Time-Series Modelling

Rough Transformers for Continuous and Efficient Time-Series Modelling

15 March 2024

Fernando Moreno-Pino

Papers citing "Rough Transformers for Continuous and Efficient Time-Series Modelling"

9 / 9 papers shown

Title
On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning Alvaro Arroyo Alessio Gravina Benjamin Gutteridge Federico Barbero Claudio Gallicchio Xiaowen Dong Michael M. Bronstein P. Vandergheynst 109 10 0 15 Feb 2025
Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data Fernando Moreno-Pino María Martínez-García Pablo Martínez Olmos Antonio Artés-Rodríguez 21 2 0 08 Nov 2022
Diffuser: Efficient Transformers with Multi-hop Attention Diffusion for Long Sequences Aosong Feng Irene Li Yuang Jiang Rex Ying 42 18 0 21 Oct 2022
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling Tung Nguyen Aditya Grover BDL UQCV 68 106 0 09 Jul 2022
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations Nabeel Seedat F. Imrie Alexis Bellot Zhaozhi Qian M. Schaar OOD CML 45 52 0 16 Jun 2022
Neural Rough Differential Equations for Long Time Series James Morrill C. Salvi Patrick Kidger James Foster Terry Lyons AI4TS 66 132 0 17 Sep 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 92 470 0 18 May 2020
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 Wang Xifeng Yan AI4TS 79 1,410 0 29 Jun 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 368 5,081 0 19 Jun 2018