Publications related to Déjà Vu: Uncanny and Serendipitous Re-encountering of Audiovisual Archives

Related publications (10)

Label Critic: Design Data Before Models

As medical datasets rapidly expand, creating detailed annotations of different body structures becomes increasingly expensive and time-consuming. We consider that requesting radiologists to create detailed annotations is unnecessarily burdensome and that p ...

IEEE Computer Society2025

Adaptive Test-Time Learning Under Domain Shift: From Augmentation to Prolonged Adaptation

Devavrat Tomar

Deep neural networks often fail to generalize when deployed in dynamic and unpredictable real-world environments, where data distributions at test time can differ significantly from those encountered during training. Since simulating all possible distribut ...

EPFL2025

Automated Ensemble Multimodal Machine Learning for Healthcare

Lucas Salomon Brunschwig

The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches generally issue predictions using data from a single modality. This stan ...

2025

Resource-efficient photonic networks for next-generation AI computing

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç, Ilker Oguz, Mustafa Yildirim, Jih-Liang Hsieh

Current trends in artificial intelligence toward larger models demand a rethinking of both hardware and algorithms. Photonics-based systems offer high-speed, energy-efficient computing units, provided algorithms are designed to exploit photonics' unique st ...

SPRINGERNATURE2025

Generative spatial artificial intelligence for sustainable smart cities: A pioneering large flow model for urban digital twin

Paul Erich Keel, Jeffrey Huang, Simon Elias Bibri

Rapid urbanization, alongside escalating resource depletion and ecological degradation, underscores the critical need for innovative urban development solutions. In response, sustainable smart cities are increasingly turning to cutting-edge technologies—su ...

2025

Content-Based Objective Evaluation of Artificially Generated Sign Language Videos

Neha Tarigopula

Sign language is vital for communication within the deaf and hard-of-hearing community. Avatar-based methods and deep learning techniques like Generative Adversarial Networks have shown promise in generating sign language video content. One of the challeng ...

IEEE2024

SAMPa: Sharpness-aware Minimization Parallelized

Volkan Cevher, Thomas Michaelsen Pethick, Wanyun Xie

Sharpness-aware minimization (SAM) has been shown to improve the generalization of neural networks. However, each SAM update requires sequentially computing two gradients, effectively doubling the per-iteration cost compared to base optimizers like SGD. We ...

2024

Towards Practical Homomorphic Aggregation in Byzantine-Resilient Distributed Learning

Rachid Guerraoui, John Stephan

The growing availability of distributed data has led to the increased use of machine learning (ML) algorithms in distributed topologies, where multiple nodes collaborate to train models under the coordination of a central server. However, distributed learn ...

Association for Computing Machinery, Inc2024

Backpropagation-free Training of Analog AI Accelerators

Romain Christophe Rémy Fleury, Ali Momeni, Matthieu Francis Malléjac

Deep learning has achieved remarkable success in diverse fields in recent years. However, this growth presents significant challenges, particularly in terms of energy consumption during both training and inference phases. While there have been efforts to i ...

Institute of Electrical and Electronics Engineers Inc.2024

IRL-Net: Inpainted Region Localization Network via Spatial Attention

Hatef Otroshi Shahreza

Identifying manipulated regions in images is a challenging task due to the existence of very accurate image inpainting techniques leaving almost unnoticeable traces in tampered regions. These image inpainting methods can be used for multiple purposes (e.g. ...

2023