5 citations · 5 across the 6 of their papers we have counts for
6 papers
Building Machine Learning Challenges for Anomaly Detection in Science
Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova +148
Scientific discoveries are often made by finding a pattern or object that was not predicted by the known rules of science. Oftentimes, these anomalous events or objects that do not…
DeepGrav: Anomalous Gravitational-Wave Detection Through Deep Latent Features
Jianqi Yan, Alex P. Leung, Zhiyuan Pei +2
This work introduces a novel deep learning-based approach for gravitational wave anomaly detection, aiming to overcome the limitations of traditional matched filtering techniques i…
Measurements of Cosmic Proton Flux through Neutron Monitors Using Deep Networks and Imputation Techniques in the AMS-02 Era
Pengwei Zhao, Jianqi Yan, Alex P. Leung +1
Accurate measurements of cosmic proton flux are essential for studying the modulation processes of cosmic rays during the solar activity cycle. A proton flux measurement method, ba…
A Stock Price Prediction Approach Based on Time Series Decomposition and Multi-Scale CNN using OHLCT Images
Zhiyuan Pei, Jianqi Yan, Jin Yan +5
Recently, deep learning in stock prediction has become an important branch. Image-based methods show potential by capturing complex visual patterns and spatial correlations, offeri…
Modeling the Time Evolution of Compact Binary Systems with Machine Learning
Jianqi Yan, Junjie Luo, Yifan Zeng +4
This work introduces advanced computational techniques for modeling the time evolution of compact binary systems using machine learning. The dynamics of compact binary systems, suc…
Autoregressive Search of Gravitational Waves: Denoising
Sangin Kim, C. Y. Hui, Jianqi Yan +5
Because of the small strain amplitudes of gravitational-wave (GW) signals, unveiling them in the presence of detector/environmental noise is challenging. For visualizing the signal…