119 citations · 151 across the 9 of their papers we have counts for
10 papers
Navigating the Metric Maze: A Taxonomy of Evaluation Metrics for Anomaly Detection in Time Series
Sondre Sørbø, Massimiliano Ruocco
The field of time series anomaly detection is constantly advancing, with several methods available, making it a challenge to determine the most appropriate method for a specific do…
Persistence Initialization: A novel adaptation of the Transformer architecture for Time Series Forecasting
Espen Haugsdal, Erlend Aune, Massimiliano Ruocco
Time series forecasting is an important problem, with many real world applications. Ensembles of deep neural networks have recently achieved impressive forecasting accuracy, but su…
Positional Encoding Augmented GAN for the Assessment of Wind Flow for Pedestrian Comfort in Urban Areas
Henrik Hoeiness, Kristoffer Gjerde, Luca Oggiano +2
Approximating wind flows using computational fluid dynamics (CFD) methods can be time-consuming. Creating a tool for interactively designing prototypes while observing the wind flo…
Augmented Memory Networks for Streaming-Based Active One-Shot Learning
Andreas Kvistad, Massimiliano Ruocco, Eliezer de Souza da Silva +1
One of the major challenges in training deep architectures for predictive tasks is the scarcity and cost of labeled training data. Active Learning (AL) is one way of addressing thi…
Dual Active Sampling on Batch-Incremental Active Learning
Johan Phan, Massimiliano Ruocco, Francesco Scibilia
Recently, Convolutional Neural Networks (CNNs) have shown unprecedented success in the field of computer vision, especially on challenging image classification tasks by relying on…
Time is of the Essence: a Joint Hierarchical RNN and Point Process Model for Time and Item Predictions
Bjørnar Vassøy, Massimiliano Ruocco, Eliezer de Souza da Silva +1
In recent years session-based recommendation has emerged as an increasingly applicable type of recommendation. As sessions consist of sequences of events, this type of recommendati…