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Found 6 papers, 3 papers with code
From Variability to Stability: Advancing RecSys Benchmarking Practices
In the rapidly evolving domain of Recommender Systems (RecSys), new algorithms frequently claim state-of-the-art performance based on evaluations over a limited set of arbitrarily selected datasets.
GCT-TTE: Graph Convolutional Transformer for Travel Time Estimation
This paper introduces a new transformer-based model for the problem of travel time estimation.
Ranked #1 on
Travel Time Estimation
on TTE-A&O
Revising deep learning methods in parking lot occupancy detection
Parking guidance systems have recently become a popular trend as a part of the smart cities' paradigm of development.
Ranked #1 on
Parking Space Occupancy
on PKLot
(F1-score metric)
5q032e@SMM4H'22: Transformer-based classification of premise in tweets related to COVID-19
Automation of social network data assessment is one of the classic challenges of natural language processing.
Logistics, Graphs, and Transformers: Towards improving Travel Time Estimation
The problem of travel time estimation is widely considered as the fundamental challenge of modern logistics.
Ranked #2 on
Travel Time Estimation
on TTE-A&O
Hybrid Graph Embedding Techniques in Estimated Time of Arrival Task
Recently, deep learning has achieved promising results in the calculation of Estimated Time of Arrival (ETA), which is considered as predicting the travel time from the start point to a certain place along a given path.
