Publications related to Rote learning

Optimizing Dynamic Aperture Studies with Active Learning

Davide Di Croce, Tatiana Pieloni, Ekaterina Krymova, Massimo Giovannozzi

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

2024

Work in progress: Imagining / Designing informal spaces for learning.

Ingrid Le Duc

The paper presents ICAP (interactive, constructive, active and passive) as the theoretical framework to understand the role of informal learning spaces as an active learning tool when students have informal meetings to work on projects. Students in our En ...

Aalborg Universitetsforlag2023

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

François Maréchal, Julia Granacher

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

Oxford2023

Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

Sokseiha Muy, Tian Xie

Data-driven approaches based on high-throughput capabilities and machine learning hold promise in revolutionizing human-centred materials discovery for sustainability and decarbonization. This Review examines the strengths and limitations of different trad ...

NATURE PORTFOLIO2022

VL4Pose: Active Learning Through Out-Of-Distribution Detection For Pose Estimation

Alexandre Massoud Alahi, Megh Hiren Shukla

Advances in computing have enabled widespread access to pose estimation, creating new sources of data streams. Unlike mock set-ups for data collection, tapping into these data streams through on-device active learning allows us to directly sample from the ...

BMVA Press2022

Active Learning for Imbalanced Civil Infrastructure Data

Diego Matteo Antognini, Adelmo Cristiano Innocenza Malossi, Ioana Giurgiu

Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we are working towards fully automating the visual inspections to support the pr ...

2022

Active learning for multi-objective optimization of processes and energy systems

François Maréchal, Julia Granacher

In superstructure optimization of processes and energy systems, the design space is defined as the combination of unit considerations, process conditions and model parameters that might be subjected to uncertainty. Most of the time, decision makers are not ...

Elsevier Science2022

Active Learning of Bayesian Probabilistic Movement Primitives

Jean-Marc Odobez, Sylvain Calinon, Hakan Girgin, Thibaut Antoine Kulak

Learning from Demonstration permits non-expert users to easily and intuitively reprogram robots. Among approaches embracing this paradigm, probabilistic movement primitives (ProMPs) are a well-established and widely used method to learn trajectory distribu ...

IEEE2021

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Rote learning

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Optimizing Dynamic Aperture Studies with Active Learning

Work in progress: Imagining / Designing informal spaces for learning.

Action Levers towards Sustainable Wellbeing: Re-Thinking Negative Emissions, Sufficiency, Deliberative Democracy

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

VL4Pose: Active Learning Through Out-Of-Distribution Detection For Pose Estimation

Active Learning for Imbalanced Civil Infrastructure Data

Active learning for multi-objective optimization of processes and energy systems

Active Learning of Bayesian Probabilistic Movement Primitives

Graph Chatbot

Chat with Graph Search

Work in progress: Imagining / Designing informal spaces for learning.

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

VL4Pose: Active Learning Through Out-Of-Distribution Detection For Pose Estimation

Active Learning for Imbalanced Civil Infrastructure Data

Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

Active learning for multi-objective optimization of processes and energy systems

Active Learning of Bayesian Probabilistic Movement Primitives

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering