56 citations · 298 across the 31 of their papers we have counts for
8 papers · 1 filter
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting
Xu Liu, Yutong Xia, Yuxuan Liang +7
Road traffic forecasting plays a critical role in smart city initiatives and has experienced significant advancements thanks to the power of deep learning in capturing non-linear p…
Graph Neural Processes for Spatio-Temporal Extrapolation
Junfeng Hu, Yuxuan Liang, Zhencheng Fan +3
We study the task of spatio-temporal extrapolation that generates data at target locations from surrounding contexts in a graph. This task is crucial as sensors that collect data a…
Do We Really Need Graph Neural Networks for Traffic Forecasting?
Xu Liu, Yuxuan Liang, Chao Huang +4
Spatio-temporal graph neural networks (STGNN) have become the most popular solution to traffic forecasting. While successful, they rely on the message passing scheme of GNNs to est…
DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models
Haomin Wen, Youfang Lin, Yutong Xia +4
Spatio-temporal graph neural networks (STGNN) have emerged as the dominant model for spatio-temporal graph (STG) forecasting. Despite their success, they fail to model intrinsic un…
Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference
Junfeng Hu, Yuxuan Liang, Zhencheng Fan +3
Sensors are the key to environmental monitoring, which impart benefits to smart cities in many aspects, such as providing real-time air quality information to assist human decision…
When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?
Xu Liu, Yuxuan Liang, Chao Huang +3
Deep learning models are modern tools for spatio-temporal graph (STG) forecasting. Though successful, we argue that data scarcity is a key factor limiting their recent improvements…
Learning based Methods for Code Runtime Complexity Prediction
Jagriti Sikka, Kushal Satya, Yaman Kumar +3
Predicting the runtime complexity of a programming code is an arduous task. In fact, even for humans, it requires a subtle analysis and comprehensive knowledge of algorithms to pre…
Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition
Yaman Kumar, Dhruva Sahrawat, Shubham Maheshwari +5
Visual Speech Recognition (VSR) is the process of recognizing or interpreting speech by watching the lip movements of the speaker. Recent machine learning based approaches model VS…