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Found 7 papers, 2 papers with code
Navigating Beyond Dropout: An Intriguing Solution Towards Generalizable Image Super Resolution
Deep learning has led to a dramatic leap on Single Image Super-Resolution (SISR) performances in recent years.
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention
Recent years have witnessed the great potential of attention mechanism in graph representation learning.
Multitask Weakly Supervised Learning for Origin Destination Travel Time Estimation
Subsequently, a Multitask Weakly Supervised Learning Framework for Travel Time Estimation (MWSL TTE) has been proposed to infer transition probability between roads segments, and the travel time on road segments and intersection simultaneously.
Easy Begun is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout
Spatial-temporal (ST) graph modeling, such as traffic speed forecasting and taxi demand prediction, is an important task in deep learning area.
GOF-TTE: Generative Online Federated Learning Framework for Travel Time Estimation
However, building a model for such a data-driven task requires a large amount of users' travel information, which directly relates to their privacy and thus is less likely to be shared.
Route to Time and Time to Route: Travel Time Estimation from Sparse Trajectories
In this case, this paper aims to resolve the problem of travel time estimation (TTE) and route recovery in sparse scenarios, which often leads to the uncertain label of travel time and route between continuously sampled GPS points.
ST-ExpertNet: A Deep Expert Framework for Traffic Prediction
Recently, forecasting the crowd flows has become an important research topic, and plentiful technologies have achieved good performances.
