activity
20212023
most citedCOCOA: Cross Modality Contrastive Learning for Sensor Data

86 citations · 106 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2023

Human Mobility Question Answering (Vision Paper)

Hao Xue, Flora D. Salim

Question answering (QA) systems have attracted much attention from the artificial intelligence community as they can learn to answer questions based on the given knowledge source (…

cs.LG20232 cited

Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: Benchmarking energy load forecasting models without and with continual learning

Arian Prabowo, Kaixuan Chen, Hao Xue +2

In traditional deep learning algorithms, one of the key assumptions is that the data distribution remains constant during both training and deployment. However, this assumption bec…

cs.LG20234 cited

Message Passing Neural Networks for Traffic Forecasting

Arian Prabowo, Hao Xue, Wei Shao +2

A road network, in the context of traffic forecasting, is typically modeled as a graph where the nodes are sensors that measure traffic metrics (such as speed) at that location. Tr…

cs.LG2023

Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study

Jason Liu, Shohreh Deldari, Hao Xue +2

In the context of mobile sensing environments, various sensors on mobile devices continually generate a vast amount of data. Analyzing this ever-increasing data presents several ch…

cs.LG202313 cited

Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting

Arian Prabowo, Wei Shao, Hao Xue +2

Traffic forecasting is a critical task to extract values from cyber-physical infrastructures, which is the backbone of smart transportation. However owing to external contexts, the…

cs.CV202286 cited

COCOA: Cross Modality Contrastive Learning for Sensor Data

Shohreh Deldari, Hao Xue, Aaqib Saeed +2

Self-Supervised Learning (SSL) is a new paradigm for learning discriminative representations without labelled data and has reached comparable or even state-of-the-art results in co…