Arian Prabowo

According to our database, Arian Prabowo authored at least 26 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

From XXLTraffic to EvoXXLTraffic: Scaling Traffic Forecasting to Sensor-Evolving Networks.

Du Yin, Hao Xue, Arian Prabowo, Shuang Ao, Flora Salim

CoRR, May, 2026

TrajDLM: Topology-Aware Block Diffusion Language Model for Trajectory Generation.

Wilson Wongso, Lihuan Li, Arian Prabowo, Xiachong Lin, Baiyu Chen, Hao Xue, Flora D. Salim

CoRR, May, 2026

2025

Electric Vehicle Charging Load Modeling: A Survey, Trends, Challenges and Opportunities.

Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, Flora D. Salim

CoRR, November, 2025

There is No "apple" in Timeseries: Rethinking TSFM through the Lens of Invariance.

Arian Prabowo, Flora D. Salim

CoRR, October, 2025

Double-Diffusion: Diffusion Conditioned Diffusion Probabilistic Model For Air Quality Prediction.

Hanlin Dong, Arian Prabowo, Hao Xue, Flora D. Salim

CoRR, June, 2025

Embedding spatial context in urban traffic forecasting with contrastive pre-training.

Matthew Low, Arian Prabowo, Hao Xue, Flora Salim

CoRR, March, 2025

A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings.

Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, Flora D. Salim

IEEE Pervasive Comput., 2025

Brick-by-Brick: Cyber-Physical Building Data Classification Challenge.

Arian Prabowo, Xiachong Lin, Imran Razzak, Hao Xue, Matthew Amos, Stephen D. White, Flora D. Salim

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

XXLTraffic: Expanding and Extremely Long Traffic Forecasting beyond Test Adaptation.

Du Yin, Hao Xue, Arian Prabowo, Shuang Ao, Flora Salim

Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems, 2025

2024

Traffic forecasting on new roads using spatial contrastive pre-training (SCPT).

Arian Prabowo, Hao Xue, Wei Shao, Piotr Koniusz, Flora D. Salim

Data Min. Knowl. Discov., May, 2024

Exploring Capabilities of Time Series Foundation Models in Building Analytics.

Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, Flora D. Salim

CoRR, 2024

XXLTraffic: Expanding and Extremely Long Traffic Dataset for Ultra-Dynamic Forecasting Challenges.

Du Yin, Hao Xue, Arian Prabowo, Shuang Ao, Flora D. Salim

CoRR, 2024

BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics.

Arian Prabowo, Xiachong Lin, Imran Razzak, Hao Xue, Emily W. Yap, Matthew Amos, Flora D. Salim

CoRR, 2024

A Gap in Time: The Challenge of Processing Heterogeneous IoT Point Data in Buildings.

Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, Stephen D. White, Flora D. Salim

CoRR, 2024

Building Timeseries Dataset: Empowering Large-Scale Building Analytics.

Arian Prabowo, Xiachong Lin, Imran Razzak, Hao Xue, Emily W. Yap, Matthew Amos, Flora D. Salim

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

BiTSA: Leveraging Time Series Foundation Model for Building Energy Analytics.

Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, Flora D. Salim

Proceedings of the IEEE International Conference on Data Mining, 2024

Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned.

Du Yin, Jinliang Deng, Shuang Ao, Zechen Li, Hao Xue, Arian Prabowo, Renhe Jiang, Xuan Song, Flora D. Salim

Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

2023

Message Passing Neural Networks for Traffic Forecasting.

Arian Prabowo, Hao Xue, Wei Shao, Piotr Koniusz, Flora D. Salim

CoRR, 2023

Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training.

Arian Prabowo, Wei Shao, Hao Xue, Piotr Koniusz, Flora D. Salim

CoRR, 2023

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, Subbu Sethuvenkatraman, Flora D. Salim

Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, 2023

Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting.

Arian Prabowo, Kaixuan Chen, Hao Xue, Subbu Sethuvenkatraman, Flora D. Salim

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

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

Arian Prabowo, Wei Shao, Hao Xue, Piotr Koniusz, Flora D. Salim

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation, 2023

2022

Generative Adversarial Networks for Spatio-temporal Data: A Survey.

Nan Gao, Hao Xue, Wei Shao, Sichen Zhao, Kyle Kai Qin, Arian Prabowo, Mohammad Saiedur Rahaman, Flora D. Salim

ACM Trans. Intell. Syst. Technol., 2022

Predicting flight delay with spatio-temporal trajectory convolutional network and airport situational awareness map.

Wei Shao, Arian Prabowo, Sichen Zhao, Piotr Koniusz, Flora D. Salim

Neurocomputing, 2022

2019

COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference.

Arian Prabowo, Piotr Koniusz, Wei Shao, Flora D. Salim

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, 2019

Flight Delay Prediction using Airport Situational Awareness Map.

Wei Shao, Arian Prabowo, Sichen Zhao, Siyu Tan, Piotr Koniusz, Jeffrey Chan, Xinhong Hei, Bradley Feest, Flora D. Salim

Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019