Publication

Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

Publications associées (32)

Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

Robustness of medical image classification models is limited by its exposure to the candidate disease classes. Generalized zero shot learning (GZSL) aims at correctly predicting seen and unseen classes and most current GZSL approaches have focused on the s ...

Springer International Publishing Ag2023

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Leonardo Petrini

Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...

EPFL2023

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

Active Learning for Imbalanced Civil Infrastructure Data

Ioana Giurgiu, Adelmo Cristiano Innocenza Malossi, Diego Matteo Antognini

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

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

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Pierre Dillenbourg, Mortadha Abderrahim, Jauwairia Nasir, Aditi Kothiyal

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

2022

Integrated Model for Comprehensive Digital Education Platforms

Denis Gillet, Isabelle Barbara Marie-Hélène Cardia, Kim Lan Phan Hoang, Maria Jesus Rodriguez Triana, Juan Carlos Farah

The trend towards generalized blended and active learning approaches in engineering education is redefining the requirements and the deployment schemes for digital education platforms. This paper presents a quadriptych techno- pedagogical model highlightin ...

IEEE2022

Promoting Computational Thinking Skills in Non-Computer Science Students Gamifying Computational Notebooks to Increase Student Engagement

Pascal Felber, Denis Gillet, Adrian Christian Holzer, Juan Carlos Farah, Marc Lafuente Martinez

Computational thinking (CT) skills are becoming increasingly relevant for future professionals across all domains, beyond computer science (CS). As such, an increasing number of bachelor and masters programs outside of the computer science discipline integ ...

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

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Democratizing Machine Learning

Alexandre David Olivier Maurer, Nirupam Gupta, Rafaël Benjamin Pinot

The increasing prevalence of personal devices motivates the design of algorithms that can leverage their computing power, together with the data they generate, in order to build privacy-preserving and effective machine learning models. However, traditional ...

IEEE2022

Reinforcement Learning for the occupant-centric operation of building energy systems: Theoretical and experimental investigations

Amirreza Heidari

Occupant behavior, defined as the presence and energy-related actions of occupants, is today known as a key driver of building energy use. Closing the gap between what is provided by building energy systems and what is actually needed by occupants requires ...

EPFL2022