4 citations · 9 across the 6 of their papers we have counts for
11 papers
FREQuency ATTribution: benchmarking frequency-based occlusion for time series data
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
Deep neural networks are among the most successful algorithms in terms of performance and scalability across different domains. However, since these networks are black boxes, their…
Utilizing Out-Domain Datasets to Enhance Multi-Task Citation Analysis
Dominique Mercier, Syed Tahseen Raza Rizvi, Vikas Rajashekar +2
Citations are generally analyzed using only quantitative measures while excluding qualitative aspects such as sentiment and intent. However, qualitative aspects provide deeper insi…
Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods
Dominique Mercier, Jwalin Bhatt, Andreas Dengel +1
In the last decade neural network have made huge impact both in industry and research due to their ability to extract meaningful features from imprecise or complex data, and by ach…
TimeREISE: Time-series Randomized Evolving Input Sample Explanation
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
Deep neural networks are one of the most successful classifiers across different domains. However, due to their limitations concerning interpretability their use is limited in safe…
PatchX: Explaining Deep Models by Intelligible Pattern Patches for Time-series Classification
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
The classification of time-series data is pivotal for streaming data and comes with many challenges. Although the amount of publicly available datasets increases rapidly, deep neur…
Interpreting Deep Models through the Lens of Data
Dominique Mercier, Shoaib Ahmed Siddiqui, Andreas Dengel +1
Identification of input data points relevant for the classifier (i.e. serve as the support vector) has recently spurred the interest of researchers for both interpretability as wel…