10 citations · 12 across the 4 of their papers we have counts for
4 papers
Training state-of-the-art pathology foundation models with orders of magnitude less data
Mikhail Karasikov, Joost van Doorn, Nicolas Känzig +5
The field of computational pathology has recently seen rapid advances driven by the development of modern vision foundation models (FMs), typically trained on vast collections of p…
Towards Large-Scale Training of Pathology Foundation Models
kaiko. ai, Nanne Aben, Edwin D. de Jong +7
Driven by the recent advances in deep learning methods and, in particular, by the development of modern self-supervised learning algorithms, increased interest and efforts have bee…
Communication-Efficient Jaccard Similarity for High-Performance Distributed Genome Comparisons
Maciej Besta, Raghavendra Kanakagiri, Harun Mustafa +4
The Jaccard similarity index is an important measure of the overlap of two sets, widely used in machine learning, computational genomics, information retrieval, and many other area…
Inverse Protein Folding Problem via Quadratic Programming
Andrii Riazanov, Mikhail Karasikov, Sergei Grudinin
This paper presents a method of reconstruction a primary structure of a protein that folds into a given geometrical shape. This method predicts the primary structure of a protein a…