no code implementations • 15 Jul 2024 • Sean Dewar, Georg Grasegger, Kaie Kubjas, Fatemeh Mohammadi, Anthony Nixon
This article considers the problem of 3-dimensional genome reconstruction for single-cell data, and the uniqueness of such reconstructions in the setting of haploid organisms.
no code implementations • 1 Feb 2024 • Kaie Kubjas, Jiayi Li, Maximilian Wiesmann
The dimension serves as a geometric measure for the expressivity of the network, the learning degree is a measure for the complexity of training the network and provides upper bounds on the number of learnable functions.
1 code implementation • 27 Jan 2023 • Diego Cifuentes, Jan Draisma, Oskar Henriksson, Annachiara Korchmaros, Kaie Kubjas
The 3-dimensional (3D) structure of the genome is of significant importance for many cellular processes.
1 code implementation • 10 Jun 2022 • Kaie Kubjas, Olga Kuznetsova, Elina Robeva, Pardis Semnani, Luca Sodomaco
We study the problem of maximum likelihood estimation of densities that are log-concave and lie in the graphical model corresponding to a given undirected graph $G$.
1 code implementation • 13 Jan 2021 • Anastasiya Belyaeva, Kaie Kubjas, Lawrence J. Sun, Caroline Uhler
A standard approach is to transform the contact frequencies into noisy distance measurements and then apply semidefinite programming (SDP) formulations to obtain the 3D configuration.
no code implementations • 14 May 2020 • Muhammad Ardiyansyah, Dimitra Kosta, Kaie Kubjas
To showcase our main result on model embeddability, we provide an application to hachimoji models, which are eight-state models for synthetic DNA.