A Metric for Phylogenetic Trees Based on Matching

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Glacier-fed streams are the cold, ultra-oligotrophic, and unstable streams that are fed by glacial meltwater. Despite these extreme conditions, they harbour a diverse and abundant microbial diversity that develops into biofilms, covering the boulders and s ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second order structure, if present. These tasks can be seen as an Analysis of Vari ...

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

Urban proximity planning is foreseen as a solution to foster a “sustainable” city, including economic viability, environmental soundness and social inclusivity. This paper focuses on the inclusivity aspects by questioning the adoption of urban proximities: ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

The Mycobacterium tuberculosis complex (MTBC) comprises nine human-adapted lineages that differ in their geographical distribution. Local adaptation of specific MTBC genotypes to the respective human host population has been invoked in this context. We aim ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Local and global inference methods have been developed to infer structural contacts from multiple sequence alignments of homologous proteins. They rely on correlations in amino acid usage at contacting sites. Because homologous proteins share a common ance ...

In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...

Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

We construct a measure on the thick points of a Brownian loop soup in a bounded domain D

D

of the plane with given intensity theta>0

\theta >0

, which is formally obtained by exponentiating the square root of its occupation field. The measure is construct ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

A Metric for Phylogenetic Trees Based on Matching

Chat with Graph Search

The microbial genomics of glacier-fed streams: adaptations to an extreme ecosystem

Extensions of Peer Prediction Incentive Mechanisms

Reliable data-driven decision-making through optimal transport

Transportation-based functional ANOVA and PCA for covariance operators

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Planning urban proximities: An empirical analysis of how residential preferences conflict with the urban morphologies and residential practices

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Bacterial diversity dominates variable macrophage responses of tuberculosis patients in Tanzania

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Room-temperature quantum optomechanics using an ultralow noise cavity

Impact of phylogeny on structural contact inference from protein sequence data

Fairness and Explainability in Clustering Problems

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining

Dynamism in the context of views out: A literature review

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Multiplicative chaos of the Brownian loop soup

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment