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09/15/2023
MAPLE: Mobile App Prediction Leveraging Large Language model Embeddings
Despite the rapid advancement of mobile applications, predicting app usa...
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09/08/2023
Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: A Continual Learning Approach Leveraging Human Mobility
In traditional deep learning algorithms, one of the key assumptions is t...
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06/10/2023
Continually learning out-of-distribution spatiotemporal data for robust energy forecasting
Forecasting building energy usage is essential for promoting sustainabil...
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05/09/2023
Message Passing Neural Networks for Traffic Forecasting
A road network, in the context of traffic forecasting, is typically mode...
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05/09/2023
Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training
New roads are being constructed all the time. However, the capabilities ...
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05/01/2023
Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study
In the context of mobile sensing environments, various sensors on mobile...
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02/20/2023
Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting
Traffic forecasting is a critical task to extract values from cyber-phys...
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12/07/2022
CrossPyramid: Neural Ordinary Differential Equations Architecture for Partially-observed Time-series
Ordinary Differential Equations (ODE)-based models have become popular f...
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09/20/2022
PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting
This paper studies the time series forecasting problem from a whole new ...
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09/11/2022
Leveraging Language Foundation Models for Human Mobility Forecasting
In this paper, we propose a novel pipeline that leverages language found...
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07/31/2022
COCOA: Cross Modality Contrastive Learning for Sensor Data
Self-Supervised Learning (SSL) is a new paradigm for learning discrimina...
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06/06/2022
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data
Recently, Self-Supervised Representation Learning (SSRL) has attracted m...
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12/14/2021
Event-Aware Multimodal Mobility Nowcasting
As a decisive part in the success of Mobility-as-a-Service (MaaS), spati...
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12/13/2021
Translating Human Mobility Forecasting through Natural Language Generation
Existing human mobility forecasting models follow the standard design of...
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09/30/2021
PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series
Heterogeneity and irregularity of multi-source data sets present a signi...
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09/30/2021
MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction
Human mobility prediction is a core functionality in many location-based...
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05/17/2021
Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classification
The usage of smartphone-collected respiratory sound, trained with deep l...
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11/28/2020
Time-series Change Point Detection with Self-Supervised Contrastive Predictive Coding
Change Point Detection techniques aim to capture changes in trends and s...
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11/11/2020
TRAILER: Transformer-based Time-wise Long Term Relation Modeling for Citywide Traffic Flow Prediction
Traffic flow prediction is a crucial task in enabling efficient intellig...
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10/12/2020
Scene Gated Social Graph: Pedestrian Trajectory Prediction Based on Dynamic Social Graphs and Scene Constraints
Pedestrian trajectory prediction is valuable for understanding human mot...
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08/18/2020
Generative Adversarial Networks for Spatio-temporal Data: A Survey
Generative Adversarial Networks (GANs) have shown remarkable success in ...
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04/21/2020