A decoder-only foundation model for time-series forecasting
Motivated by recent advances in large language models for Natural Language Processing
(NLP), we design a time-series foundation model for forecasting whose out-of-the-box zero …
(NLP), we design a time-series foundation model for forecasting whose out-of-the-box zero …
Weather4cast at neurips 2022: Super-resolution rain movie prediction under spatio-temporal shifts
Weather4cast again advanced modern algorithms in AI and machine learning through a
highly topical interdisciplinary competition challenge: The prediction of hi-res rain radar …
highly topical interdisciplinary competition challenge: The prediction of hi-res rain radar …
Traffic4cast at neurips 2021-temporal and spatial few-shot transfer learning in gridded geo-spatial processes
C Eichenberger, M Neun, H Martin… - NeurIPS 2021 …, 2022 - proceedings.mlr.press
The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks
can successfully predict future traffic conditions 1 hour into the future on simply aggregated …
can successfully predict future traffic conditions 1 hour into the future on simply aggregated …
Spatiotemporal prediction of microstructure evolution with predictive recurrent neural network
AAK Farizhandi, M Mamivand - Computational Materials Science, 2023 - Elsevier
Prediction of microstructure evolution during material processing is essential to control the
material properties. Simulation tools for microstructure evolution prediction based on …
material properties. Simulation tools for microstructure evolution prediction based on …
Urban traffic forecasting using federated and continual learning
Smart cities are instrumented with several types pf sensors, which allow to transmit,
elaborate and exploit the collected data for different services. In this paper we focus on the …
elaborate and exploit the collected data for different services. In this paper we focus on the …
Metropolitan segment traffic speeds from massive floating car data in 10 cities
Traffic analysis is crucial for urban operations and planning, while the availability of dense
urban traffic data beyond loop detectors is still scarce. We present a large-scale floating …
urban traffic data beyond loop detectors is still scarce. We present a large-scale floating …
Pauli gaussian fibonacci and pauli gaussian lucas quaternions
AZ Azak - Mathematics, 2022 - mdpi.com
We have investigated new Pauli Fibonacci and Pauli Lucas quaternions by taking the
components of these quaternions as Gaussian Fibonacci and Gaussian Lucas numbers …
components of these quaternions as Gaussian Fibonacci and Gaussian Lucas numbers …
Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction
C Feng, L Huang, D Krompass - arXiv preprint arXiv:2402.07570, 2024 - arxiv.org
We present General Time Transformer (GTT), an encoder-only style foundation model for
zero-shot multivariate time series forecasting. GTT is pretrained on a large dataset of 200M …
zero-shot multivariate time series forecasting. GTT is pretrained on a large dataset of 200M …
Deep Hypercomplex Networks for Spatiotemporal Data Processing: Parameter efficiency and superior performance [Hypercomplex Signal and Image Processing]
A Bojesomo, P Liatsis… - IEEE Signal Processing …, 2024 - ieeexplore.ieee.org
Hypercomplex numbers, such as quaternions and octonions, have recently gained attention
because of their advantageous properties over real numbers, eg, in the development of …
because of their advantageous properties over real numbers, eg, in the development of …
SwinUNet3D--A Hierarchical Architecture for Deep Traffic Prediction using Shifted Window Transformers
Traffic forecasting is an important element of mobility management, an important key that
drives the logistics industry. Over the years, lots of work have been done in Traffic …
drives the logistics industry. Over the years, lots of work have been done in Traffic …