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Arian Prabowo
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Year
Generative adversarial networks for spatio-temporal data: A survey
N Gao, H Xue, W Shao, S Zhao, KK Qin, A Prabowo, MS Rahaman, ...
ACM Transactions on Intelligent Systems and Technology (TIST) 13 (2), 1-25, 2022
982022
Flight delay prediction using airport situational awareness map
W Shao, A Prabowo, S Zhao, S Tan, P Koniusz, J Chan, X Hei, B Feest, ...
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances …, 2019
342019
Predicting flight delay with spatio-temporal trajectory convolutional network and airport situational awareness map
W Shao, A Prabowo, S Zhao, P Koniusz, FD Salim
Neurocomputing 472, 280-293, 2022
332022
Coltrane: Convolutional trajectory network for deep map inference
A Prabowo, P Koniusz, W Shao, FD Salim
Proceedings of the 6th ACM international conference on systems for energy …, 2019
172019
Because every sensor is unique, so is every pair: Handling dynamicity in traffic forecasting
A Prabowo, W Shao, H Xue, P Koniusz, FD Salim
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and …, 2023
102023
Traffic forecasting on new roads using spatial contrastive pre-training (SCPT)
A Prabowo, H Xue, W Shao, P Koniusz, FD Salim
Data Mining and Knowledge Discovery 38 (3), 913-937, 2024
7*2024
Continually learning out-of-distribution spatiotemporal data for robust energy forecasting
A Prabowo, K Chen, H Xue, S Sethuvenkatraman, FD Salim
arXiv preprint arXiv:2306.06385, 2023
52023
Message Passing Neural Networks for Traffic Forecasting
A Prabowo, H Xue, W Shao, P Koniusz, FD Salim
arXiv preprint arXiv:2305.05740, 2023
42023
Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: Benchmarking energy load forecasting models without and with continual learning
A Prabowo, K Chen, H Xue, S Sethuvenkatraman, FD Salim
Proceedings of the 10th ACM International Conference on Systems for Energy …, 2023
2*2023
Spatiotemporal deep learning
A Prabowo
PhD thesis, RMIT University, 2022
22022
A Gap in Time: The Challenge of Processing Heterogeneous IoT Point Data in Buildings
X Lin, A Prabowo, I Razzak, H Xue, M Amos, S Behrens, S White, ...
arXiv preprint arXiv:2405.14267, 2024
12024
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned
D Yin, J Deng, S Ao, Z Li, H Xue, A Prabowo, R Jiang, X Song, F Salim
arXiv preprint arXiv:2406.12709, 2024
2024
XXLTraffic: Expanding and Extremely Long Traffic Dataset for Ultra-Dynamic Forecasting Challenges
D Yin, H Xue, A Prabowo, S Ao, F Salim
arXiv preprint arXiv:2406.12693, 2024
2024
BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics
A Prabowo, X Lin, I Razzak, H Xue, EW Yap, M Amos, FD Salim
arXiv preprint arXiv:2406.08990, 2024
2024
Revisiting Traffic Forecasting from a PINN Perspective
A Prabowo, FD Salim
2023
Correction to: Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting
A Prabowo, K Chen, H Xue, S Sethuvenkatraman, FD Salim
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023
2023
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