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S. O’Banion

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG3

identity via Semantic Scholar / OpenAlex

most citedDeep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case

353 citations · 503 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2024

UserSumBench: A Benchmark Framework for Evaluating User Summarization Approaches

Chao Wang, Neo Wu, Lin Ning +5

Large language models (LLMs) have shown remarkable capabilities in generating user summaries from a long list of raw user activity data. These summaries capture essential user info…

cs.LG2022

Smartphone-based Hard-braking Event Detection at Scale for Road Safety Services

Luyang Liu, David Racz, Kara Vaillancourt +9

Road crashes are the sixth leading cause of lost disability-adjusted life-years (DALYs) worldwide. One major challenge in traffic safety research is the sparsity of crashes, which…

cs.LG2020★ 150 cited

Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks

Amol Kapoor, Xue Ben, Luyang Liu +4

In this work, we examine a novel forecasting approach for COVID-19 case prediction that uses Graph Neural Networks and mobility data. In contrast to existing time series forecastin…

cs.LG2020★ 353 cited

Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case

Neo Wu, Bradley Green, Xue Ben +1

In this paper, we present a new approach to time series forecasting. Time series data are prevalent in many scientific and engineering disciplines. Time series forecasting is a cru…

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