15 citations · 31 across the 6 of their papers we have counts for
7 papers
Model Agnostic Explainable Selective Regression via Uncertainty Estimation
Andrea Pugnana, Carlos Mougan, Dan Saattrup Nielsen
With the wide adoption of machine learning techniques, requirements have evolved beyond sheer high performance, often requiring models to be trustworthy. A common approach to incre…
ScandEval: A Benchmark for Scandinavian Natural Language Processing
Dan Saattrup Nielsen
This paper introduces a Scandinavian benchmarking platform, ScandEval, which can benchmark any pretrained model on four different tasks in the Scandinavian languages. The datasets…
Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agenda
Andrés Domínguez Hernández, Richard Owen, Dan Saattrup Nielsen +1
Machine learning (ML) enabled classification models are becoming increasingly popular for tackling the sheer volume and speed of online misinformation and other content that could…
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset
Dan Saattrup Nielsen, Ryan McConville
Misinformation is becoming increasingly prevalent on social media and in news articles. It has become so widespread that we require algorithmic assistance utilising machine learnin…
Monitoring Model Deterioration with Explainable Uncertainty Estimation via Non-parametric Bootstrap
Carlos Mougan, Dan Saattrup Nielsen
Monitoring machine learning models once they are deployed is challenging. It is even more challenging to decide when to retrain models in real-case scenarios when labeled data is b…
The Virtual Large Cardinal Hierarchy
Stamatis Dimopoulos, Victoria Gitman, Dan Saattrup Nielsen
We continue the study of the virtual large cardinal hierarchy by analysing virtual versions of superstrong, Woodin, and Berkeley cardinals. Gitman and Schindler showed that virtual…
Games and Ramsey-like cardinals
Dan Saattrup Nielsen, Philip Welch
We generalise the -Ramsey cardinals introduced in Holy and Schlicht (2018) for cardinals to arbitrary ordinals , and answer several questions posed in that paper. In part…