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On Computing Breakpoint Distances for Genomes with Duplicate Genes

Related publications (28)

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

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 ...

EPFL2024

Learning to Remove Cuts in Integer Linear Programming

Volkan Cevher, Grigorios Chrysos, Efstratios Panteleimon Skoulakis

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

2024

Comparison of Three Viral Nucleic Acid Preamplification Pipelines for Sewage Viral Metagenomics

Tamar Kohn, Xavier Fernandez Cassi

Viral metagenomics is a useful tool for detecting multiple human viruses in urban sewage. However, more refined protocols are required for its effective use in disease surveillance. In this study, we investigated the performance of three different preampli ...

2024

Molecular hypergraph neural networks

Philippe Schwaller, Junwu Chen

Graph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as m ...

Aip Publishing2024

Adaptive projected variational quantum dynamics

Giuseppe Carleo, David Linteau, Stefano Barison

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

Amer Physical Soc2024

Isogeny Problems with Level Structure

Tako Boris Fouotsa

Given two elliptic curves and the degree of an isogeny between them, finding the isogeny is believed to be a difficult problem—upon which rests the security of nearly any isogeny-based scheme. If, however, to the data above we add information about the beh ...

2024

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Alexander Carl Unnervik

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

Gibbs sampling the posterior of neural networks

Lenka Zdeborová, Emanuele Troiani, Giovanni Piccioli

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Iop Publishing Ltd2024

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024