most citedMeasuring Financial Time Series Similarity With a View to Identifying Profitable Stock Market Opportunities

8 citations · 17 across the 5 of their papers we have counts for

collaborators

7 papers

q-fin.ST20226 cited

Stock Embeddings: Learning Distributed Representations for Financial Assets

Rian Dolphin, Barry Smyth, Ruihai Dong

Identifying meaningful relationships between the price movements of financial assets is a challenging but important problem in a variety of financial applications. However with rec…

cs.LG2022

NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-task Financial Forecasting

Linyi Yang, Jiazheng Li, Ruihai Dong +2

Financial forecasting has been an important and active area of machine learning research because of the challenges it presents and the potential rewards that even minor improvement…

cs.HC20212 cited

Investigating Health-Aware Smart-Nudging with Machine Learning to Help People Pursue Healthier Eating-Habits

Mansura A Khan, Khalil Muhammad, Barry Smyth +1

Food-choices and eating-habits directly contribute to our long-term health. This makes the food recommender system a potential tool to address the global crisis of obesity and maln…

q-fin.ST20218 cited

Measuring Financial Time Series Similarity With a View to Identifying Profitable Stock Market Opportunities

Rian Dolphin, Barry Smyth, Yang Xu +1

Forecasting stock returns is a challenging problem due to the highly stochastic nature of the market and the vast array of factors and events that can influence trading volume and…

cs.AI2021

Handling Climate Change Using Counterfactuals: Using Counterfactuals in Data Augmentation to Predict Crop Growth in an Uncertain Climate Future

Mohammed Temraz, Eoin Kenny, Elodie Ruelle +3

Climate change poses a major challenge to humanity, especially in its impact on agriculture, a challenge that a responsible AI should meet. In this paper, we examine a CBR system (…

cs.LG2021

If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques

Mark T Keane, Eoin M Kenny, Eoin Delaney +1

In recent years, there has been an explosion of AI research on counterfactual explanations as a solution to the problem of eXplainable AI (XAI). These explanations seem to offer te…