We have a new paper with the title “Statistical guarantees for sparse deep learning” in AStA Adv. Stat. Anal.
Category Archives: New Paper
Approximate Stationary Points of Simple Neural Networks
Our new paper “Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks” is now online. Well done, Mahsa and Fang! 🎉🎉
New Paper on Variable Clustering
We have a new paper “VC-PCR: a prediction method based on supervised variable selection and clustering” about variable clustering in transcriptomics and in general. Great work especially from Rebecca, who just defended her PhD, and from Rainer and Bernadette, the two other members of our Belgian🇧🇪-American🇺🇸-German🇩🇪 tag team!
Depth Normalization of Small RNA Sequencing
Our paper “Depth Normalization of Small RNA Sequencing: Using Data and Biology to Select a Suitable Method” is now available on arXiv. Great to work with you, Yannick and Li-Xuan! 🦠
Normalizing Flows
We have submitted a new paper “copula-based normalizing flows.” Great to work with you, Mike and Asja! ☄️
Vanishing gradients
We have analized the vanishing-gradient problem in deep learning and potential remedies here. Congratulations, Leni! 🏄
Two new papers on deep learning
We two new papers on deep learning, one on targeted deep learning and one on robust deep learning. Well done, Shih-Ting!
Activation Functions in Artificial Neural Networks
We have composed an overview of activation functions in artificial neural networks here.
Optimization landscapes in deep learning
We analyze the optimization landscapes of feedforward neural networks here. We show especially that the landscapes of wide networks do not have spurious local minima.
Statistics and artificial intelligence
We have discussed the role of statistics in artificial intelligence here.