Zero-shot forecasting of chaotic systems

24 September 2024

Papers citing "Zero-shot forecasting of chaotic systems"

22 / 72 papers shown

Title
Next Generation Reservoir Computing D. Gauthier Erik Bollt Aaron Griffith W. A. S. Barbosa 73 410 0 14 Jun 2021
Monash Time Series Forecasting Archive Rakshitha Godahewa Christoph Bergmeir Geoffrey I. Webb Rob J. Hyndman Pablo Montero-Manso AI4TS 65 159 0 14 May 2021
RoFormer: Enhanced Transformer with Rotary Position Embedding Jianlin Su Yu Lu Shengfeng Pan Ahmed Murtadha Bo Wen Yunfeng Liu 278 2,453 0 20 Apr 2021
Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps Ren-Chuen Chen Molei Tao 55 52 0 09 Mar 2021
Modern Koopman Theory for Dynamical Systems Steven L. Brunton M. Budišić E. Kaiser J. Nathan Kutz AI4CE 97 417 0 24 Feb 2021
Machine learning prediction of critical transition and system collapse Ling-Wei Kong Hua-wei Fan C. Grebogi Y. Lai 43 85 0 02 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 497 2,414 0 18 Oct 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 109 312 0 24 Sep 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 762 42,055 0 28 May 2020
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization Rui Wang Robin Walters Rose Yu AI4CE 111 175 0 08 Feb 2020
Meta-learning framework with applications to zero-shot time-series forecasting Boris N. Oreshkin Dmitri Carpov Nicolas Chapados Yoshua Bengio UQCV AI4TS AI4CE 204 112 0 07 Feb 2020
Deep Double Descent: Where Bigger Models and More Data Hurt Preetum Nakkiran Gal Kaplun Yamini Bansal Tristan Yang Boaz Barak Ilya Sutskever 119 942 0 04 Dec 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 424 20,181 0 23 Oct 2019
Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics Pantelis R. Vlachas Jaideep Pathak Brian R. Hunt T. Sapsis M. Girvan Edward Ott Petros Koumoutsakos AI4TS 61 391 0 09 Oct 2019
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 107 1,416 0 29 Jun 2019
Gated recurrent units viewed through the lens of continuous time dynamical systems I. Jordan Piotr A. Sokól Il Memming Park 47 58 0 03 Jun 2019
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting Boris N. Oreshkin Dmitri Carpov Nicolas Chapados Yoshua Bengio AI4TS 110 1,054 0 24 May 2019
Shaping the learning landscape in neural networks around wide flat minima Carlo Baldassi Fabrizio Pittorino R. Zecchina MLT 69 83 0 20 May 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 232 1,650 0 28 Dec 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 414 5,111 0 19 Jun 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 701 131,652 0 12 Jun 2017
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,882 0 12 Nov 2013