Concept

Framework

Publications associées (27)

A general framework to evaluate different rebalancing operations strategies in one-way car sharing systems

Michel Bierlaire, Selin Ataç, Nikola Obrenovic

Car sharing systems (CSSs) are one of the environmentally beneficial solutions in urban transportation. However, the operators still struggle to make these systems profitable. One of the main contributors in operational cost is rebalancing operations. Ther ...

2022

Data-driven distributed online learning control for islanded microgrids

Alireza Karimi, Seyed Sohail Madani, Dongdong Zheng

In this paper, a new discrete-time data-driven distributed learning control strategy for frequency/voltage regulation and active/reactive power sharing of islanded microgrids is proposed. Instead of using the static droop relationship and the conventional ...

2022

Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities

Alexandre Schmid

Unstructured neural network pruning algorithms have achieved impressive compression ratios. However, the resulting-typically irregular-sparse matrices hamper efficient hardware implementations, leading to additional memory usage and complex control logic t ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Towards Beam-Beam Simulations for FCC-ee

Xavier Buffat, Tatiana Pieloni, Mike Seidel, Giovanni Iadarola, Péter Kicsiny

The FCC-ee (Future Circular Collider) lepton collider is currently the most favored next generation research infrastructure project at CERN, aimed at studying properties of standard model particles with the highest precision ever. The chosen parameters of ...

JACoW Publishing, Geneva, Switzerland2022

Recursive Input And State Estimation: A General Framework For Learning From Time Series With Missing Data

Robert West, Alberto Garcia Duran

Time series with missing data are signals encountered in important settings for machine learning. Some of the most successful prior approaches for modeling such time series are based on recurrent neural networks that transform the input and previous state ...

IEEE2021

Learning the Exciton Properties of Azo-dyes

Anne-Clémence Corminboeuf, Alberto Fabrizio, Sergio Vela Llausi, Ksenia Briling

The ab initio determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine l ...

AMER CHEMICAL SOC2021

Vehicle sharing systems: A review and a holistic management framework

Michel Bierlaire, Selin Ataç, Nikola Obrenovic

Although different vehicle sharing systems (VSSs) use different vehicle types, the management challenges and optimization problems to be solved are similar or even the same. This observation led us to create a generalized and holistic VSS management framew ...

2021

Grid-aware Distributed Model Predictive Control of Heterogeneous Resources in a Distribution Network: Theory and Experimental Validation

Mario Paolone, Fabrizio Sossan, Rahul Kumar Gupta

In this paper, we propose and experimentally validate a scheduling and control framework for distributed energy resources (DERs) that achieves to track a day-ahead dispatch plan of a distribution network hosting controllable and stochastic heterogeneous re ...

2020

Data Handling in Industry 4.0: Interoperability Based on Distributed Ledger Technology

Information-intensive transformation is vital to realize the Industry 4.0 paradigm, where processes, systems, and people are in a connected environment. Current factories must combine different sources of knowledge with different technological layers. Taki ...

2020

Model-based predictive control methods for distributed energy resources in smart grids

Luca Fabietti

This thesis develops optimization-based techniques for the control of distributed energy resources to provide multiple services to the power network. It is divided into three parts. The first part of this thesis focuses on the development of a framework f ...

EPFL2019

Representations and descriptors unifying the study of molecular and bulk systems

Kevin Rossi

Establishing a unified framework for describing the structures of molecular and periodic systems is a long-standing challenge in physics, chemistry, and material science. With the rise of machine learning methods in these fields, there is a growing need fo ...

WILEY2019

Artist Residencies for Innovation: Development of a Global Framework

Nicolas Henchoz, Pierre-Xavier Georges Adrien Puissant

Artists can play a major role in the success of innovation. The European program STARTS aims to increase their impact in high-tech environments. An international consortium has the mission to implement 45 residencies and set a complete framework for such p ...

ASSOC COMPUTING MACHINERY2019

Appearance of polished 18 karat gold surfaces: linking aesthetics to surface features

Leili Batooli

Impeccable appearance of surfaces is a key constraint in high-end jewelry and watch manufacturing. Based on long tradition in the industry, appearance of products is assessed by trained individuals through visual inspection in designated intervals on the p ...

EPFL2019

Placement of Virtual Containers on NUMA systems: A Practical and Comprehensive Model

Baptiste Joseph Eustache Lepers

Our work addresses the problem of placement of threads, or virtual cores, onto physical cores in a multicore NUMA system. Different placements result in varying degrees of contention for shared resources, so choosing the right placement can have a large ef ...

USENIX ASSOC2018

DESIA: A General Framework for Designing Interlocking Assemblies

Mark Pauly, Ziqi Wang, Peng Song

Interlocking assemblies have a long history in the design of puzzles, furniture, architecture, and other complex geometric structures. The key defining property of interlocking assemblies is that all component parts are immobilized by their geometric arran ...

ASSOC COMPUTING MACHINERY2018

DESIA: A General Framework for Designing Interlocking Assemblies

Mark Pauly, Ziqi Wang, Peng Song

2018

Machine learning unifies the modeling of materials and molecules

Michele Ceriotti, Sandip De

Determining the stability ofmolecules and condensed phases is the cornerstone of atomisticmodeling, underpinning our understanding of chemical andmaterials properties and transformations. We show that amachine-learningmodel, based on a local description of ...

Amer Assoc Advancement Science2017

A General Framework for Sensor Placement in Source Localization

Patrick Thiran, Laura Elisa Celis, Brunella Marta Spinelli

When an epidemic spreads in a given network of individuals or communities, can we detect its source using only the information provided by a small set of nodes? We propose a general framework that incorporates two dimensions. First, we can either rely excl ...

2019

Spline Shape Processing : Representation, Learning, and Modeling

Daniel Andreas Schmitter

In this thesis, we present a novel generic and unifying framework for data-adaptive shape modeling. Our work is motivated by the raising need for powerful geometric modeling kernels that are required for shape characterization in biomedical imaging. The on ...

EPFL2017

Analysis, Optimization, and Modeling of Analog Multi-Tone Serial Data Transceivers

Yusuf Leblebici, Gain Kim, Kiarash Gharibdoust

This paper presents a versatile and fast time-domain architectural modeling framework for high-speed serial data transceivers (TRX) that can employ various analog modulation schemes. We highlight a modeling of TRXs employing an analog multi-tone signaling, ...

2017