no code implementations • 14 Dec 2023 • Anton Shapkin, Denis Litvinov, Yaroslav Zharov, Egor Bogomolov, Timur Galimzyanov, Timofey Bryksin
Our approach achieves several targets: (1) lifting the length limitations of the context window, saving on the prompt size; (2) allowing huge expansion of the number of retrieval entities available for the context; (3) alleviating the problem of misspelling or failing to find relevant entity names.
no code implementations • 25 Mar 2023 • Yaroslav Zharov, Evelina Ametova, Rebecca Spiecker, Tilo Baumbach, Genoveva Burca, Vincent Heuveline
For such imaging techniques, the method can therefore significantly improve image quality, or maintain image quality with further reduced exposure time per image.
no code implementations • 24 Mar 2023 • Yaroslav Zharov, Tilo Baumbach, Vincent Heuveline
In Computed Tomography, machine learning is often used for automated data processing.
no code implementations • 24 Feb 2023 • Jwalin Bhatt, Yaroslav Zharov, Sungho Suh, Tilo Baumbach, Vincent Heuveline, Paul Lukowicz
Morphological atlases are an important tool in organismal studies, and modern high-throughput Computed Tomography (CT) facilities can produce hundreds of full-body high-resolution volumetric images of organisms.
no code implementations • 17 Mar 2022 • Yaroslav Zharov, Alexey Ershov, Tilo Baumbach, Vincent Heuveline
In this work, we propose a pre-training method SortingLoss.
no code implementations • 6 Nov 2020 • Yaroslav Zharov, Alexey Ershov, Tilo Baumbach, Vincent Heuveline
The problem is even more prominent for high-throughput tomography--an automated setup, capable of scanning large batches of samples without human interaction.
no code implementations • 7 Nov 2018 • Yaroslav Zharov, Denis Korzhenkov, Pavel Shvechikov, Alexander Tuzhilin
We introduce a novel approach to feed-forward neural network interpretation based on partitioning the space of sequences of neuron activations.