Target group: Researchers, PhD students from Nordic universities, developers, data scientists and other interested people from the public sector may participate.
This is the third workshop dedicated to GraphNeT – Graph neural networks for neutrino telescope event reconstruction. The goal is to bring together researchers working at the intersection of neutrino telescope experiments and machine learning to discuss the latest progress and develop new solutions to physics challenges using graph neural networks (GNNs). Target group: Participants […]
The 2023 RecSys summer school will be held from Monday June 12th to Friday June 16th in Copenhagen, Denmark. Leaders in the field will give lectures on the practice, research, and state of the art in recommender systems. The lectures are covering a broad range of topics from an algorithmic as well as an methodological […]
The Danish-Swedish summer school on TDA and spatial statistics is a five-day event with the aim of educating data scientists to work at the interface of Topological Data Analysis (TDA) and Spatial Statistics. The principal target group are PhD students and postdocs in data science and related subjects; practitioners from industry are also highly welcome. […]
Target group: PhD students within both methodological and applied data science research for whom generative modelling potentially plays a part in their PhD projects. + Postdocs and senior researchers who want to work with deep generative models, as well as people from the industry as continual training in data science. Will be promoted through the […]
The International Conference for Computational Social Science (IC2S2) will be held at the Mærsk Tower of the University of Copenhagen, July 17-20, 2023. IC2S2 has emerged as the dominant conference at the intersection of social and computational science, bringing together researchers from around the world in economics, sociology, political science, psychology, cognitive science, management, computer […]
Missing data is a common problem in image processing and in general AI based methods. The source can be, for example, occlusions in 3D computer vision problems, poorly dyed tissue in biological applications, missing data points in long-term observations, or perhaps there is just too little annotated data for a deep-learning model to properly converge. […]