Viability Principles for Constrained Optimization Using a (1+1)-CMA-ES

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Using Enterprise Models to Explain and Discuss Autopoiesis and Homeostasis in Socio-technical Systems

The article links two seemingly different fundamental theoretical concepts of autopoiesis and homeostasis and tries to apply them to the realm of socio-technical systems with the use of the Fractal Enterprise Model (FEM). Autopoiesis is the property of a s ...

2020

From Classical to Unsupervised-Deep-Learning Methods for Solving Inverse Problems in Imaging

Harshit Gupta

In this thesis, we propose new algorithms to solve inverse problems in the context of biomedical images. Due to ill-posedness, solving these problems require some prior knowledge of the statistics of the underlying images. The traditional algorithms, in th ...

EPFL2020

Protein Structural Information and Evolutionary Landscape by In Vitro Evolution

Paolo De Los Rios

Protein structure is tightly intertwined with function according to the laws of evolution. Understanding how structure determines function has been the aim of structural biology for decades. Here, we have wondered instead whether it is possible to exploit ...

OXFORD UNIV PRESS2020

Accelerating materials discovery for solid state electrolytes

Matthieu Gilles Mottet

The development of new solid-state electrolytes is a key step in improving the performance and safety of battery technology. Although the use of first-principle methods has proved invaluable in better understanding the process at play in these materials, ...

EPFL2020

IMPACT: Interval-based Multi-pass Proteomic Alignment with Constant Traceback

James Richard Larus, Sahand Kashani, Stuart Anthony Byma

Darwin is a genomics co-processor that achieved a 15000x acceleration on long read assembly through innovative hardware and algorithm co-design. Darwins algorithms and hardware implementation were specifically designed for DNA analysis pipelines. This pape ...

2019

The influence of limited visual sensing on the Reynolds ﬂocking algorithm

Dario Floreano, Fabrizio Schiano, Enrica Soria

The interest in multi-drone systems flourished in the last decade and their application is promising in many fields. We believe that in order to make drone swarms flying smoothly and reliably in real-world scenarios we need a first intermediate step which ...

2019

The Minimization of Public Facilities With Enhanced Genetic Algorithms Using War Elimination

Michael Mark

In this paper, we focus on the problem of minimizing a network of state facilities that provide essential public services (schools, offices, and hospitals). The goal is to reduce the size of the network in order to minimize the costs associated with it. Ho ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Linking a mutation to survival in wild mice

Jeffrey David Jensen, Matthieu Foll, Susanne Petra Pfeifer, Stefan Jean Laurent

Adaptive evolution in new or changing environments can be difficult to predict because the functional connections between genotype, phenotype, and fitness are complex. Here, we make these explicit connections by combining field and laboratory experiments i ...

American Association for the Advancement of Science2019

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

Ilija Bogunovic

The central task in many interactive machine learning systems can be formalized as the sequential optimization of a black-box function. Bayesian optimization (BO) is a powerful model-based framework for \emph{adaptive} experimentation, where the primary go ...

EPFL2019

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