no code implementations • 23 May 2024 • Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, Stephen White, Flora D. Salim
The growing need for sustainable energy solutions has driven the integration of digitalized buildings into the power grid, utilizing Internet-of-Things technology to optimize building performance and energy efficiency.
1 code implementation • 19 Apr 2024 • Peibo Li, Maarten de Rijke, Hao Xue, Shuang Ao, Yang song, Flora D. Salim
Our results show that the proposed framework outperforms the state-of-the-art models in all three datasets.
no code implementations • 6 Mar 2024 • Hao Xue, Tianye Tang, Ali Payani, Flora D. Salim
Specifically, the framework includes a prompt generation stage based on the information entropy of prompts and a prompt refinement stage to integrate mechanisms such as the chain of thought.
1 code implementation • 19 Feb 2024 • Ruiyi Yang, Flora D. Salim, Hao Xue
Our framework offers a simple but comprehensive way to understand the underlying patterns and trends in dynamic KG, thereby enhancing the accuracy of predictions and the relevance of recommendations.
no code implementations • 6 Dec 2023 • Aaron J. Snoswell, Lucinda Nelson, Hao Xue, Flora D. Salim, Nicolas Suzor, Jean Burgess
Generic `toxicity' classifiers continue to be used for evaluating the potential for harm in natural language generation, despite mounting evidence of their shortcomings.
1 code implementation • 26 Oct 2023 • Hao Xue, Flora D. Salim
Energy load forecasting plays a crucial role in optimizing resource allocation and managing energy consumption in buildings and cities.
2 code implementations • 24 Oct 2023 • Yonchanok Khaokaew, Kaixin Ji, Thuc Hanh Nguyen, Hiruni Kegalle, Marwah Alaofi, Hao Xue, Flora D. Salim
This paper explores the intersection of technology and sleep pattern comprehension, presenting a cutting-edge two-stage framework that harnesses the power of Large Language Models (LLMs).
no code implementations • 2 Oct 2023 • Hao Xue, Flora D. Salim
The aim of the task is to let the intelligent system learn from mobility data and answer related questions.
1 code implementation • 15 Sep 2023 • Yonchanok Khaokaew, Hao Xue, Flora D. Salim
This study introduces a novel prediction model, Mobile App Prediction Leveraging Large Language Model Embeddings (MAPLE), which employs Large Language Models (LLMs) and installed app similarity to overcome these challenges.
1 code implementation • 8 Sep 2023 • Arian Prabowo, KaiXuan Chen, Hao Xue, Subbu Sethuvenkatraman, Flora D. Salim
In traditional deep learning algorithms, one of the key assumptions is that the data distribution remains constant during both training and deployment.
1 code implementation • 10 Jun 2023 • Arian Prabowo, KaiXuan Chen, Hao Xue, Subbu Sethuvenkatraman, Flora D. Salim
One of the primary reasons for this is the shift in distribution of occupancy patterns, with many people working or learning from home.
1 code implementation • 9 May 2023 • Arian Prabowo, Hao Xue, Wei Shao, Piotr Koniusz, Flora D. Salim
During inference, the spatial encoder only requires two days of traffic data on the new roads and does not require any re-training.
no code implementations • 9 May 2023 • Arian Prabowo, Hao Xue, Wei Shao, Piotr Koniusz, Flora D. Salim
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.
no code implementations • 1 May 2023 • Jason Liu, Shohreh Deldari, Hao Xue, Van Nguyen, Flora D. Salim
In the context of mobile sensing environments, various sensors on mobile devices continually generate a vast amount of data.
no code implementations • 21 Feb 2023 • Renhao Huang, Hao Xue, Maurice Pagnucco, Flora Salim, Yang song
Trajectory prediction is an important task to support safe and intelligent behaviours in autonomous systems.
1 code implementation • 20 Feb 2023 • Arian Prabowo, Wei Shao, Hao Xue, Piotr Koniusz, Flora D. Salim
Further analysis also shows that each pair of sensors also has a unique dynamic.
no code implementations • 7 Dec 2022 • Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim
In this article, we introduce CrossPyramid, a novel ODE-based model that aims to enhance the generalizability of sequences representation.
2 code implementations • 20 Sep 2022 • Hao Xue, Flora D. Salim
In this novel task, the numerical input and output are transformed into prompts and the forecasting task is framed in a sentence-to-sentence manner, making it possible to directly apply language models for forecasting purposes.
1 code implementation • 11 Sep 2022 • Hao Xue, Bhanu Prakash Voutharoja, Flora D. Salim
In this paper, we propose a novel pipeline that leverages language foundation models for temporal sequential pattern mining, such as for human mobility forecasting tasks.
1 code implementation • 31 Jul 2022 • Shohreh Deldari, Hao Xue, Aaqib Saeed, Daniel V. Smith, Flora D. Salim
Contrastive Learning (CL) is one of the most well-known approaches in SSL that attempts to learn general, informative representations of data.
no code implementations • 6 Jun 2022 • Shohreh Deldari, Hao Xue, Aaqib Saeed, Jiayuan He, Daniel V. Smith, Flora D. Salim
Unlike existing reviews of SSRL that have pre-dominately focused upon methods in the fields of CV or NLP for a single modality, we aim to provide the first comprehensive review of multimodal self-supervised learning methods for temporal data.
1 code implementation • 14 Dec 2021 • Zhaonan Wang, Renhe Jiang, Hao Xue, Flora D. Salim, Xuan Song, Ryosuke Shibasaki
As a decisive part in the success of Mobility-as-a-Service (MaaS), spatio-temporal predictive modeling for crowd movements is a challenging task particularly considering scenarios where societal events drive mobility behavior deviated from the normality.
no code implementations • NeurIPS 2021 • Hao Xue, Flora D. Salim, Yongli Ren, Nuria Oliver
Furthermore, unlike existing methods, we introduce a location prediction branch in MobTCast as an auxiliary task to model the geographical context and predict the next location.
no code implementations • 30 Sep 2021 • Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim
Heterogeneity and irregularity of multi-source data sets present a significant challenge to time-series analysis.
no code implementations • 17 May 2021 • Hao Xue, Flora D. Salim
The pre-trained feature encoder is then fine-tuned in the downstream phase to perform cough classification.
2 code implementations • 28 Nov 2020 • Shohreh Deldari, Daniel V. Smith, Hao Xue, Flora D. Salim
Change Point Detection (CPD) methods identify the times associated with changes in the trends and properties of time series data in order to describe the underlying behaviour of the system.
no code implementations • 11 Nov 2020 • Hao Xue, Flora D Salim
A Transformer based long-term relation prediction module is explicitly designed to discover the periodicity and enable the three components to be jointly modeled This module predicts the periodic relation which is then used to yield the predicted urban flow tensor.
no code implementations • 12 Oct 2020 • Hao Xue, Du Q. Huynh, Mark Reynolds
We compare our SGSG against twenty state-of-the-art pedestrian trajectory prediction methods and the results show that the proposed method achieves superior performance on two widely used trajectory prediction benchmarks.
no code implementations • 18 Aug 2020 • Nan Gao, Hao Xue, Wei Shao, Sichen Zhao, Kyle Kai Qin, Arian Prabowo, Mohammad Saiedur Rahaman, Flora D. Salim
Generative Adversarial Networks (GANs) have shown remarkable success in producing realistic-looking images in the computer vision area.
no code implementations • 21 Apr 2020 • Hao Xue, Du. Q. Huynh, Mark Reynolds
Pedestrian trajectory prediction is a challenging task as there are three properties of human movement behaviors which need to be addressed, namely, the social influence from other pedestrians, the scene constraints, and the multimodal (multiroute) nature of predictions.