Advancing a Multimodal 3D Motions Library for DanceForms™

Leveraging its roots in dance and technology, Credo is building a multimodal motions platform for dance to enhance education, choreography and archival practices; the foundation being motion capture data. There are existing 3D motion capture libraries but they are either one of or many of the following: outdated, not comprehensive, poor quality, non-standard, poorly labelled […]

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élaboration d’un modèle de prévisions du comportement des utilisateurs chez Readygg

Ce projet vise à soutenir Readygg dans ses efforts en développant un système de collecte de données fiable et performant adapté aux contraintes du blockchain. Ce système permettra une meilleure compréhension et réponse aux tendances de consommation des joueurs dans l’écosystème Web3. De plus, le développement d’outils pour le suivi et l’analyse des indicateurs clés […]

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A Group Recommender System for deviantART

deviantART is the world’s largest online arts community with a huge number of users and items. They currently recommend art to users only via an algorithmic presentation of “popular” items, and an item-item recommender system presented alongside every individual piece of art. deviantART expects to use recommender systems technology to enhance and leverage the contributions […]

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Algorithmic auditing through synthetic data

Algorithm auditing refers to the study and evaluation of algorithmic systems to ensure their transparency, fairness, legality and compliance with ethical standards. Our project focuses on the acceptability of practical audits where platforms provide synthetic data about algorithms, instead of the traditional approach with external audits without considering the collaboration of the platform. Technical implications […]

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Towards Causal Deep Learning for Explainability, Robustness, and Extrapolation

In many applications, Machine Learning (ML) predictions are used to make downstream decisions. Acting on ML predictions however can change the distribution of features that the ML model relies on for predictions. The implication is that such downstream decisions procedures implicitly expect the ML model to generalize outside of the observational distribution. Unfortunately, this is […]

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Développement d’algorithmes d’IA pour soutenir le développement de médicaments oncologiques

En biologie, tout comme dans le monde des machines mécaniques, la fonction découle de la structure. Dans le domaine biologique, les “machines” sont constituées de protéines. En altérant leur structure, il est possible de leur conférer de nouvelles fonctionnalités. L’entreprise 9Bio combine une expertise de pointe en modélisation IA avec l’ingénierie structurelle biologique pour créer […]

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Quantum Machine Learning for cybersecurity

La cybersécurité est devenue une préoccupation majeure pour les entreprises et les organisations en raison de la croissance exponentielle des menaces en sécurité informatique. Internet est un élément critique qui est devenu un réseau universel de communication. Les attaques réseau, y compris les attaques par déni de service distribué (DDoS), sont considérées comme l’une des […]

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SecureMed

The healthcare sector generates an enormous amount of sensitive data, ranging from patient medical records to billing information. The mishandling or unauthorized access to such data can lead to significant legal, financial, and ethical consequences. Despite increasing awareness of the importance of data security, healthcare institutions often still employ outdated or inadequate encryption methods, posing […]

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Building Decarbonization Planning Applying Machine-learning Techniques to Building Data

In response to the escalating demand for clean tech and energy-efficient structures, our project focuses on revolutionizing building data processing for swift decarbonization planning. We tackle the challenge by parsing diverse data from mixed media documents and fine-tuning pre-trained large language models (LLMs) for optimal data query accuracy. Our approach integrates text parsing, tokenization, and […]

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Enhancing technical drawing analysis with semantic segmentation and OCR technologies

This project aims to enhance the work with technical drawings in manufacturing is done by using advanced computer techniques to automatically identify and read text within these drawings. This means turning detailed plans and sketches into digital data quickly and accurately, without manual input. For the partner organization, this innovation promises to greatly speed up […]

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