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

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

20 February 2023

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

9 / 9 papers shown

Title
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 Salim AI4TS 37 0 0 18 Jun 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 AI4TS AI4CE 29 3 0 13 Jun 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 White Flora D. Salim 21 0 0 23 May 2024
Pre-training with Random Orthogonal Projection Image Modeling Maryam Haghighat Peyman Moghadam Shaheer Mohamed Piotr Koniusz VLM 13 7 0 28 Oct 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 21 2 0 08 Sep 2023
Continually learning out-of-distribution spatiotemporal data for robust energy forecasting Arian Prabowo Kaixuan Chen Hao Xue Subbu Sethuvenkatraman Flora D. Salim OOD 18 11 0 10 Jun 2023
Traffic Forecasting on New Roads Using Spatial Contrastive Pre-Training (SCPT) Arian Prabowo Hao Xue Wei Shao Piotr Koniusz Flora D. Salim AI4TS 17 12 0 09 May 2023
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 172 1,095 0 27 Apr 2021
Tensor Representations for Action Recognition Piotr Koniusz Lei Wang A. Cherian 29 68 0 28 Dec 2020