research
∙
04/06/2023
TBDetector:Transformer-Based Detector for Advanced Persistent Threats with Provenance Graph
APT detection is difficult to detect due to the long-term latency, cover...
share
research
∙
02/23/2023
LightCTS: A Lightweight Framework for Correlated Time Series Forecasting
Correlated time series (CTS) forecasting plays an essential role in many...
research
∙
12/08/2022
AutoPINN: When AutoML Meets Physics-Informed Neural Networks
Physics-Informed Neural Networks (PINNs) have recently been proposed to ...
research
∙
11/29/2022
Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting
Sensors in cyber-physical systems often capture interconnected processes...
research
∙
08/22/2022
Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey
Deep learning technologies have demonstrated remarkable effectiveness in...
research
∙
08/11/2022
Uncertainty Quantification for Traffic Forecasting: A Unified Approach
Uncertainty is an essential consideration for time series forecasting ta...
research
∙
12/21/2021
AutoCTS: Automated Correlated Time Series Forecasting – Extended Version
Correlated time series (CTS) forecasting plays an essential role in many...
research
∙
01/21/2020
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
The vast proliferation of sensor devices and Internet of Things enables ...
research
∙
10/21/2019
Reasoning About Recursive Tree Traversals
Traversals are commonly seen in tree data structures, and performance-en...
research
∙
05/22/2019
Multi-agent Attentional Activity Recognition
Multi-modality is an important feature of sensor based activity recognit...
research
∙
11/12/2018
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing
Semi-supervised learning is crucial for alleviating labelling burdens in...
research
∙
10/04/2018
Brain2Object: Printing Your Mind from Brain Signals with Spatial Correlation Embedding
Electroencephalography (EEG) signals are known to manifest differential ...
research
∙
05/17/2018
Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling
Multimodal features play a key role in wearable sensor-based human activ...
research
∙
11/21/2017
Fullie and Wiselie: A Dual-Stream Recurrent Convolutional Attention Model for Activity Recognition
Multimodal features play a key role in wearable sensor based Human Activ...
research
∙
09/26/2017
Multi-Person Brain Activity Recognition via Comprehensive EEG Signal Analysis
An electroencephalography (EEG) based brain activity recognition is a fu...
research
∙
09/26/2017
Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signals
An electroencephalography (EEG) based Brain Computer Interface (BCI) ena...
research
∙
08/22/2017
