Concept

Evolutionary computation

Related publications (266)

The Two Times Problem: Where Is the Problem?

Gruber et al. (2022) offered a framework how to explain "Physical time within human time", solving the 'two times problem: Here, I am asking whether such a problem exists at all. To question the question, I will appeal to neurobiological, evolutionary, and ...

Brill2024

Design and experimental investigation of a herringbone grooved gas bearing supported turbocharger

Jürg Alexander Schiffmann, Wanhui Liu

The design of an oil free turbocharger supported on herringbone grooved gas bearing was formulated as a multi-objective problem, which was solved by coupling a reduced order parametric model for gas bearing supported rotors with an evolutionary algorithm. ...

2023

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Rachid Guerraoui, Andrei Kucharavy, Matteo Monti

Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms but also to a drastic increase in computational power used to train them.|S ...

New York2023

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain

The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain- ...

2023

A Framework for Autonomic Computing for In Situ Imageomics

Nina Marion Aurélia Van Tiel

In situ imageomics is a new approach to study ecological, biological and evolutionary systems wherein large image and video data sets are captured in the wild and machine learning methods are used to infer biological traits of individual organisms, animal ...

The Institute of Electrical and Electronics Engineers, Inc2023

Machine-learning predictor of nerve fiber firing rate allows the automatic optimization of electrical stimulation protocols

Silvestro Micera, Simone Romeni, Luca Pierantoni, Gabriele Marino

Computational models have been widely employed to study the electrical stimulation of the nervous system. Still, most applications either study fundamental mechanisms underlying stimulation, or address qualitative scientific questions. When quantitative qu ...

IEEE2023

Cellularization across eukaryotes: Conserved mechanisms and novel strategies

Omaya Pierre Dudin

Many eukaryotes form multinucleated cells during their devel-opment. Some cells persist as such during their lifetime, others choose to cleave each nucleus individually using a specialized cytokinetic process known as cellularization. What is cellula-rizat ...

CURRENT BIOLOGY LTD2023

Genetic Optimization of Homogeneous Catalysts

Rubén Laplaza Solanas, Simone Gallarati

We present the NaviCatGA package, a versatile genetic algorithm capable of optimizing molecular catalyst structures using well-suited fitness functions to achieve a set of targeted properties. The flexibility and generality of this tool are validated and d ...

2022

A universal workflow for creation, validation and generalization of detailed neuronal models

Henry Markram, Srikanth Ramaswamy, Werner Alfons Hilda Van Geit, Alexis Arnaudon, Maria Reva, Mustafa Anil Tuncel, Darshan Mandge, Christian Andreas Rössert, Tanguy Pierre Louis Damart

Detailed single neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools are dedicated to the reproduction of a small set of specific ...

2022

Optimization methods for collaborative learning

Sai Praneeth Reddy Karimireddy

A traditional machine learning pipeline involves collecting massive amounts of data centrally on a server and training models to fit the data. However, increasing concerns about the privacy and security of user's data, combined with the sheer growth in the ...

EPFL2021

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