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Found 5 papers, 1 papers with code
OT-Filter: An Optimal Transport Filter for Learning With Noisy Labels
Learning with noisy labels is challenging because the performance of the deep neural networks (DNN) drastically degenerates, due to confirmation bias caused by the network memorization over noisy labels.
Learn to Explore: on Bootstrapping Interactive Data Exploration with Meta-learning
The process of data exploration can be viewed as the process of training a classifier, which determines whether a database tuple is interesting to a user.
STUaNet: Understanding uncertainty in spatiotemporal collective human mobility
The high dynamics and heterogeneous interactions in the complicated urban systems have raised the issue of uncertainty quantification in spatiotemporal human mobility, to support critical decision-makings in risk-aware web applications such as urban event prediction where fluctuations are of significant interests.
Inductive Link Prediction for Nodes Having Only Attribute Information
In attributed graphs, both the structure and attribute information can be utilized for link prediction.
RiskOracle: A Minute-level Citywide Traffic Accident Forecasting Framework
Real-time traffic accident forecasting is increasingly important for public safety and urban management (e. g., real-time safe route planning and emergency response deployment).
