Sebastian Bieringer
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View article: Raising awareness of uncertain choices in empirical data analysis: A teaching concept toward replicable research practices
Raising awareness of uncertain choices in empirical data analysis: A teaching concept toward replicable research practices Open
Throughout their education and when reading the scientific literature, students may get the impression that there is a unique and correct analysis strategy for every data analysis task and that this analysis strategy will always yield a si…
View article: Classifier Surrogates: Sharing AI-based Searches with the World
Classifier Surrogates: Sharing AI-based Searches with the World Open
In recent years, neural network-based classification has been used to improve data analysis at collider experiments. While this strategy proves to be hugely successful, the underlying models are not commonly shared with the public and rely…
View article: AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization
AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization Open
Uncertainty estimation is a key issue when considering the application of deep neural network methods in science and engineering. In this work, we introduce a novel algorithm that quantifies epistemic uncertainty via Monte Carlo sampling f…
View article: The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks
The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks Open
MALA is a popular gradient-based Markov chain Monte Carlo method to access the Gibbs-posterior distribution. Stochastic MALA (sMALA) scales to large data sets, but changes the target distribution from the Gibbs-posterior to a surrogate pos…
View article: Calomplification — the power of generative calorimeter models
Calomplification — the power of generative calorimeter models Open
Motivated by the high computational costs of classical simulations, machine-learned generative models can be extremely useful in particle physics and elsewhere. They become especially attractive when surrogate models can efficiently learn …
View article: Dihydroxyquingdainone Induces Apoptosis in Leukaemia and Lymphoma Cells via the Mitochondrial Pathway in a Bcl-2- and Caspase-3-Dependent Manner and Overcomes Resistance to Cytostatic Drugs In Vitro
Dihydroxyquingdainone Induces Apoptosis in Leukaemia and Lymphoma Cells via the Mitochondrial Pathway in a Bcl-2- and Caspase-3-Dependent Manner and Overcomes Resistance to Cytostatic Drugs In Vitro Open
Isatis tinctoria and its indigo dyes have already provided highly active anti-leukaemic lead compounds, with the focus mainly being on indirubin, whereas indigo itself is inactive. There are many more indigoids to find in this plant extrac…
View article: Semi-synthetic puwainaphycin/minutissamide cyclic lipopeptides with improved antifungal activity and limited cytotoxicity
Semi-synthetic puwainaphycin/minutissamide cyclic lipopeptides with improved antifungal activity and limited cytotoxicity Open
Both the substitution of free hydroxyl substituents and extending/branching of the fatty acid moiety improved the antifungal potency and limits the cytotoxicity of cyanobacterial cyclic lipopeptides puwainaphycin/minutissamides.