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We consider a family of problems that are concerned about making predictions for the majority of unlabeled, graph-structured data samples based on a small proportion of labeled samples. Relational information among the data samples, often…

Machine Learning · Computer Science 2019-11-05 Jiaqi Ma , Weijing Tang , Ji Zhu , Qiaozhu Mei

Modern computing and communication technologies can make data collection procedures very efficient. However, our ability to analyze large data sets and/or to extract information out from them is hard-pressed to keep up with our capacities…

Machine Learning · Statistics 2019-01-30 Zhanfeng Wang , Yumi Kwon , Yuan-chin Ivan Chang

In various situations one is given only the predictions of multiple classifiers over a large unlabeled test data. This scenario raises the following questions: Without any labeled data and without any a-priori knowledge about the…

Machine Learning · Statistics 2014-10-31 Ariel Jaffe , Boaz Nadler , Yuval Kluger

Partial-label learning (PLL) is a multi-class classification problem, where each training example is associated with a set of candidate labels. Even though many practical PLL methods have been proposed in the last two decades, there lacks a…

Machine Learning · Computer Science 2020-10-26 Lei Feng , Jiaqi Lv , Bo Han , Miao Xu , Gang Niu , Xin Geng , Bo An , Masashi Sugiyama

Despite the remarkable progress in generative modelling, current diffusion models lack a quantitative approach to assess image quality. To address this limitation, we propose to estimate the pixel-wise aleatoric uncertainty during the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Michele De Vita , Vasileios Belagiannis

We consider the bifurcating Markov chain model introduced by Guyon to detect cellular aging from cell lineage. To take into account the possibility for a cell to die, we use an underlying Galton-Watson process to describe the evolution of…

Probability · Mathematics 2008-07-08 Jean-François Delmas , Laurence Marsalle

We study the asymptotic number of certain monotonically labeled increasing trees arising from a generalized evolution process. The main difference between the presented model and the classical model of binary increasing trees is that the…

Combinatorics · Mathematics 2019-10-30 Olivier Bodini , Antoine Genitrini , Bernhard Gittenberger , Stephan Wagner

Cell detection is an essential task in cell image analysis. Recent deep learning-based detection methods have achieved very promising results. In general, these methods require exhaustively annotating the cells in an entire image. If some…

Computer Vision and Pattern Recognition · Computer Science 2021-07-22 Kazuma Fujii , Daiki Suehiro , Kazuya Nishimura , Ryoma Bise

Generative models inspired by dynamical transport of measure -- such as flows and diffusions -- construct a continuous-time map between two probability densities. Conventionally, one of these is the target density, only accessible through…

Machine Learning · Computer Science 2024-09-24 Michael S. Albergo , Mark Goldstein , Nicholas M. Boffi , Rajesh Ranganath , Eric Vanden-Eijnden

Cell division times in microbial populations display significant fluctuations, that impact the population growth rate in a non-trivial way. If fluctuations are uncorrelated among different cells, the population growth rate is predicted by…

Populations and Evolution · Quantitative Biology 2021-07-07 Simone Pigolotti

In this paper, we introduce a general numerical method to approximate the reproduction numbers of a large class of multi-group, age-structured, population models with a finite age span. To provide complete flexibility in the definition of…

Populations and Evolution · Quantitative Biology 2024-03-21 Simone De Reggi , Francesca Scarabel , Rossana Vermiglio

Our purpose is to estimate the posterior distribution of the parameters of interest for controlled branching processes (CBPs) without prior knowledge of the maximum number of offspring that an individual can give birth to and without…

Methodology · Statistics 2021-08-10 Miguel González , Carmen Minuesa , Inés del Puerto

Branching processes model the evolution of populations of agents that randomly generate offsprings. These processes, more patently Galton-Watson processes, are widely used to model biological, social, cognitive, and technological phenomena,…

Applications · Statistics 2013-02-26 Fabricio Murai , Bruno Ribeiro , Don Towsley , Krista Gile

We analyze evolutionary dynamics in a confluent, branching cellular population, such as in a growing duct, vasculature, or in a branching microbial colony. We focus on the coarse-grained features of the evolution and build a statistical…

Populations and Evolution · Quantitative Biology 2022-02-15 Adam S. Bryant , Maxim O. Lavrentovich

We consider a neutral haploid population whose generations are not overlapping and whose size is large and constantly of $N$ individuals. Any generation is replaced by a new one and any individual has a single parent. We do not choose the…

Populations and Evolution · Quantitative Biology 2009-11-11 Maurizio Serva

We present modelling results that examine the consequences of implementing cumulative labelling with thymidine analogues, to estimate the cell cycle time and growth fraction of dividing cells, when the steady-state assumption is violated.…

Cell Behavior · Quantitative Biology 2019-05-30 Darragh M Walsh

A fundamental question in biology is how cell populations evolve into different subtypes based on homogeneous processes at the single cell level. Here we show that population bimodality can emerge even when biological processes are…

Molecular Networks · Quantitative Biology 2019-07-01 Jorge Fernandez-de-Cossio-Diaz , Roberto Mulet , Alexei Vazquez

Visual knowledge bases such as Visual Genome power numerous applications in computer vision, including visual question answering and captioning, but suffer from sparse, incomplete relationships. All scene graph models to date are limited to…

Computer Vision and Pattern Recognition · Computer Science 2019-12-03 Vincent S. Chen , Paroma Varma , Ranjay Krishna , Michael Bernstein , Christopher Re , Li Fei-Fei

This paper focuses on semi-supervised crowd counting, where only a small portion of the training data are labeled. We formulate the pixel-wise density value to regress as a probability distribution, instead of a single deterministic value.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-26 Hui Lin , Zhiheng Ma , Rongrong Ji , Yaowei Wang , Zhou Su , Xiaopeng Hong , Deyu Meng

In a geographically distributed population, assortative clustering plays an important role in evolution by modifying local environments. To examine its effects in a linear habitat, we consider a one-dimensional grid of cells, where each…

Populations and Evolution · Quantitative Biology 2021-03-16 Sunhee Chae , Nahyeon Lee , Seung Ki Baek , Hyeong-Chai Jeong