Search Results for author: David C. Anastasiu

Found 5 papers, 4 papers with code

Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series Forecasting

1 code implementation14 Dec 2023 Yanhong Li, Jack Xu, David C. Anastasiu

In the hydrology field, time series forecasting is crucial for efficient water resource management, improving flood and drought control and increasing the safety and quality of life for the general population.

Management Representation Learning +3

The 7th AI City Challenge

no code implementations15 Apr 2023 Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Sanjita Prajapati, Alice Li, Shangru Li, Krishna Kunadharaju, Shenxin Jiang, Rama Chellappa

The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems (ITS) - that have considerable untapped potential.

Retrieval

An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural Networks

1 code implementation29 Nov 2022 Yanhong Li, Jack Xu, David C. Anastasiu

Forecasting time series with extreme events has been a challenging and prevalent research topic, especially when the time series data are affected by complicated uncertain factors, such as is the case in hydrologic prediction.

Time Series Time Series Prediction

Cannot find the paper you are looking for? You can Submit a new open access paper.