11 citations · 15 across the 3 of their papers we have counts for
3 papers
stat.ML2022
AA-Forecast: Anomaly-Aware Forecast for Extreme Events
Ashkan Farhangi, Jiang Bian, Arthur Huang +3
Time series models often deal with extreme events and anomalies, both prevalent in real-world datasets. Such models often need to provide careful probabilistic forecasting, which i…
cs.CL2022★ 11 cited
Protoformer: Embedding Prototypes for Transformers
Ashkan Farhangi, Ning Sui, Nan Hua +3
Transformers have been widely applied in text classification. Unfortunately, real-world data contain anomalies and noisy labels that cause challenges for state-of-art Transformers.…
cs.LG2022★ 4 cited
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19
Ashkan Farhangi, Arthur Huang, Zhishan Guo
The COVID-19 pandemic has significantly impacted the tourism and hospitality sector. Public policies such as travel restrictions and stay-at-home orders had significantly affected…