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intelligent assistants | DSA Research Group - Vollmer Research Group https://sebastian.vollmer.ms/tag/intelligent-assistants/ |
Example Event | DSA Research Group - Vollmer Research Group https://sebastian.vollmer.ms/event/example/ |
DSSG Germany Summer Programme - Vollmer Research Group https://sebastian.vollmer.ms/dssgcall/TransparencyPartner2022.pdf |
DSA Research Group https://sebastian.vollmer.ms/ |
Research | DSA Research Group https://sebastian.vollmer.ms/research/ |
Sebastian Vollmer | Vollmer Research Group https://sebastian.vollmer.ms/author/sebastian-vollmer/index.xml |
Distributed Bayesian learning with stochastic natural gradient ... https://sebastian.vollmer.ms/publication/hasenclever-2017-pj/ |
Spectral gaps for a Metropolis--Hastings algorithm in infinite ... https://sebastian.vollmer.ms/publication/hairer-2014-at/ |
DSA Research Group https://sebastian.vollmer.ms/index.xml |
neural networks | Vollmer Research Group https://sebastian.vollmer.ms/tag/neural-networks/ |
"stochastic approximation" | DSA Research Group https://sebastian.vollmer.ms/tag/stochastic-approximation/ |
Raphael Sonabend | DSA Research Group https://sebastian.vollmer.ms/author/raphael-sonabend/index.xml |
Sergey Redyuk | Vollmer Research Group https://sebastian.vollmer.ms/author/sergey-redyuk/ |
L Szpruch | DSA Research Group https://sebastian.vollmer.ms/author/l-szpruch/ |
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News People Research Jobs PhD MSc DSSG Contact English Deutsch The Data Science and its Applications (DSA) Research Group is a constellation of researchers who—while geographically and institutionally spread—are united under the supervision of Professor Sebastian Vollmer , with a shared goal of advancing data science methods and tools, and using them across industrial and socially-important applications. Our main homes are the German Research Center for Artificial Intelligence (DFKI) , where we form the Data Science and its Applications research department, and the University of Kaiserslautern , where we form the Applied Machine Learning group. The currently focuses on several major streams: AI for healthcare and public policy The research group has applied machine learning methods to develop tools to generate actionable insights to inform the British government’s response to Covid-19, perform treatment selection for diabetes and predict emergency admissions in Scotland. Bayesian methodology and Monte Carlo methods The development of novel methodologies and the extension of established theoretical works pertaining to machine learning. Event analysis The interconnected problems of measuring and predicting individual and societal health and well-being, through the use of longitudinal surveys, time series and survival data to model both directly observable and latent temporal states, such as adverse health events. Machine Learning in Julia Development of the software package Machine Learning in Julia (MLJ), a modelling toolbox providing a common interface and meta-algorithms for selecting, tuning, evaluating and building composite models. Responsible AI Modern technologies introduce novel challenges in algorithmic fairness, data privacy, and scientific reproduciblity. We are developing methods to detect and mitigate ethical issues in AI-assisted processes. Data Science for Social Good We use our knowledge in these areas to champion new ways of delivering impact, through short term collaborations with industrial, nonprofit and academic partners to address real-world challenges in programs that combine training and delivery. Meet the group Find more about members of the Vollmer Research Group Meet the team We are hiring! We are looking for people on all levels to join our group. Remote options available! Jobs Data Science for Social Good Find out more about our summer fellowship More about DSSG Previous Next Latest News A visit from German Chancellor Olaf Scholz On March 18, 2022, German Chancellor Olaf Scholz visited the DFKI site in Kaiserslautern together with the Minister President of Rhineland-Palatinate, Malu Dreyer. Prof. Sebastian Vollmer at the Science and Technology Committee of the British House of Commons On Wednesday the 19th of January, 2022, Prof Sebastian Vollmer was acting as a witness in an evidence session of the UK House of Commons Science and Technology Committee on reproducibility and research integrity Neural Networks for Survival Analysis in R I have received many questions about survival neural networks (‘survival networks’) in R, ranging from is this even possible?” to how do I install Python in R?” and how can I tune these models?”. If you are an R user with an interest in survival networks then this is the article for you! Twitter internship Short account of Harry’s internship Machine Learning in Julia MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing and comparing machine learning models written in Julia and other languages. See all posts Meet the team → Impressum . © 2024 Sebastian Vollmer. This work is licensed under CC BY NC ND 4.0 . Published with Wowchemy — the free, open source website builder that empowers creators. Cite × Copy...