Chaos as an interpretable benchmark for forecasting and data-driven modelling

11 October 2021

Papers citing "Chaos as an interpretable benchmark for forecasting and data-driven modelling"

17 / 17 papers shown

Title
Optimizing Hard Thresholding for Sparse Model Discovery Derek W. Jollie Scott G. McCalla 41 0 0 28 Apr 2025
Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning Anh Tong Thanh Nguyen-Tang Dongeun Lee Duc Nguyen Toan M. Tran David Hall Cheongwoong Kang Jaesik Choi 35 0 0 03 Mar 2025
Channel Dependence, Limited Lookback Windows, and the Simplicity of Datasets: How Biased is Time Series Forecasting? Ibram Abdelmalak Kiran Madhusudhanan Jungmin Choi Maximilian Stubbemann Lars Schmidt-Thieme AI4TS 67 1 0 17 Feb 2025
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 37 4 0 24 Sep 2024
Machine Learning for Predicting Chaotic Systems Christof Schötz Alistair J R White Maximilian Gelbrecht Niklas Boers AI4CE 36 4 0 29 Jul 2024
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers Guglielmo Gattiglio Lyudmila Grigoryeva M. Tamborrino 35 1 0 20 May 2024
A projected nonlinear state-space model for forecasting time series signals Christian Donner Anuj Mishra Hideaki Shimazaki AI4TS 21 0 0 22 Nov 2023
ODEFormer: Symbolic Regression of Dynamical Systems with Transformers Stéphane d’Ascoli Soren Becker Alexander Mathis Philippe Schwaller Niki Kilbertus 29 22 0 09 Oct 2023
Variability of echo state network prediction horizon for partially observed dynamical systems Ajit Mahata Reetish Padhi A. Apte 21 1 0 19 Jun 2023
Evaluating generation of chaotic time series by convolutional generative adversarial networks Y. Tanaka Y. Yamaguti 26 2 0 26 May 2023
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics Manuela Brenner Florian Hess G. Koppe Daniel Durstewitz 28 10 0 15 Dec 2022
AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions F. Bonnet Jocelyn Ahmed Mazari Paola Cinnella Patrick Gallinari AI4CE 33 54 0 15 Dec 2022
Experimental study of Neural ODE training with adaptive solver for dynamical systems modeling A. Allauzen Thiago Petrilli Maffei Dardis Hannah Plath AI4CE 24 0 0 13 Nov 2022
Flipped Classroom: Effective Teaching for Time Series Forecasting P. Teutsch Patrick Mäder AI4TS 23 8 0 17 Oct 2022
Unsupervised Learned Kalman Filtering Guy Revach Nir Shlezinger Timur Locher Xiaoyong Ni Ruud J. G. van Sloun Yonina C. Eldar SSL 31 31 0 18 Oct 2021
KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics Guy Revach Nir Shlezinger Xiaoyong Ni Adrià López Escoriza Ruud J. G. van Sloun Yonina C. Eldar 25 264 0 21 Jul 2021
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou Shanghang Zhang J. Peng Shuai Zhang Jianxin Li Hui Xiong Wan Zhang AI4TS 169 3,900 0 14 Dec 2020