Abstract: Systems and methods for performing event prediction by: receiving an event prediction query, retrieving documents comprising information pertaining to the event prediction query, processing the documents to determine a relevance of the documents to the event prediction query, and generating an input article using the documents and the event prediction query. A decoder comprising a neural network then decodes the input vector into an event prediction outcome. The documents may be news articles. This core method may be supplemented in any one or more ways, such as by using a reward, using one or more large language models to summarize the training documents, and segmenting questions with numeric answers from those with non-numeric answers.

Abstract: Systems and methods are provided for human activity analysis and localization using channel state information (CSI). A streamlined data processing and feature extraction approach that addresses concept drifts for time series data is provided. Data obtained from CSI or any other mechanism is used to estimate the wireless channel between two different wireless nodes (e.g., an access point (AP) and an associated station (STA)), and can be used to train a robust system capable of performing room level localization. A phase and magnitude augmented feature space along with a standardization technique that is little affected by drifts is also used.

Abstract: Systems and methods are provided for human activity analysis and localization using channel state information (CSI). A streamlined data processing and feature extraction approach that addresses concept drifts for time series data is provided. Data obtained from CSI or any other mechanism is used to estimate the wireless channel between two different wireless nodes (e.g., an access point (AP) and an associated station (STA)), and can be used to train a robust system capable of performing room level localization. A phase and magnitude augmented feature space along with a standardization technique that is little affected by drifts is also used.

Abstract: Systems and methods are provided for human activity analysis and localization using channel state information (CSI). A streamlined data processing and feature extraction approach that addresses concept drifts for time series data is provided. Data obtained from CSI or any other mechanism is used to estimate the wireless channel between two different wireless nodes (e.g., an access point (AP) and an associated station (STA)), and can be used to train a robust system capable of performing room level localization. A phase and magnitude augmented feature space along with a standardization technique that is little affected by drifts is also used.