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Found 7 papers, 3 papers with code
Towards Foundation Time Series Model: To Synthesize Or Not To Synthesize?
In this work, we consider the essential question if it is advantageous to train a foundation model on synthetic data or it is better to utilize only a limited number of real-life examples.
Hiding Backdoors within Event Sequence Data via Poisoning Attacks
This adoption brings new danger, as deep black-box models are known to be vulnerable to adversarial attacks.
The Battle of Information Representations: Comparing Sentiment and Semantic Features for Forecasting Market Trends
To start, we demonstrate the connection of tweet sentiments with the volatility of companies' stock prices.
Label Attention Network for sequential multi-label classification: you were looking at a wrong self-attention
For example, the micro-AUC of our approach is $0. 9536$ compared to $0. 7501$ for a vanilla transformer.
Relationships between patenting trends and research activity for green energy technologies
Our results show that the advancement of research in all three areas of eco-innovation does not automatically lead to the increase in the number of patents.
New drugs and stock market: how to predict pharma market reaction to clinical trial announcements
The first factor is the drug portfolio size of the company, indicating the greater susceptibility to an announcement in the case of small drug diversification.
Adversarial Attacks on Deep Models for Financial Transaction Records
In this work, we examine adversarial attacks on transaction records data and defences from these attacks.
