Zobrazeno 1 - 10
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pro vyhledávání: '"Saunier P"'
We study algebraic K-theory and topological Hochschild homology in the setting of bimodules over a stable category, a datum we refer to as a laced category. We show that in this setting both K-theory and THH carry universal properties, the former def
Externí odkaz:
http://arxiv.org/abs/2411.04743
We propose a novel Transformer-based module to address the data association problem for multi-object tracking. From detections obtained by a pretrained detector, this module uses only coordinates from bounding boxes to estimate an affinity score betw
Externí odkaz:
http://arxiv.org/abs/2403.08018
Autor:
Sabri, Khalil, Djilali, Célia, Bilodeau, Guillaume-Alexandre, Saunier, Nicolas, Bouachir, Wassim
Publikováno v:
Proceedings of the 21st Conference on Robots and Vision, 2024
Urban traffic environments present unique challenges for object detection, particularly with the increasing presence of micromobility vehicles like e-scooters and bikes. To address this object detection problem, this work introduces an adapted detect
Externí odkaz:
http://arxiv.org/abs/2402.18503
Autor:
Saunier, Victor
We show that Quillen's resolution theorem for K-theory also applies to exact $\infty$-categories. We introduce heart structures on a stable $\infty$-category, generalizing weight structures, and using resolution ideas, we show that the category of st
Externí odkaz:
http://arxiv.org/abs/2311.13836
Deep learning-based multivariate and multistep-ahead traffic forecasting models are typically trained with the mean squared error (MSE) or mean absolute error (MAE) as the loss function in a sequence-to-sequence setting, simply assuming that the erro
Externí odkaz:
http://arxiv.org/abs/2212.06653
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering, 2024
Spatiotemporal traffic data imputation is of great significance in intelligent transportation systems and data-driven decision-making processes. To perform efficient learning and accurate reconstruction from partially observed traffic data, we assert
Externí odkaz:
http://arxiv.org/abs/2212.01529
The problem of broad practical interest in spatiotemporal data analysis, i.e., discovering interpretable dynamic patterns from spatiotemporal data, is studied in this paper. Towards this end, we develop a time-varying reduced-rank vector autoregressi
Externí odkaz:
http://arxiv.org/abs/2211.15482
Autor:
Carole Faviez, Xiaoyi Chen, Nicolas Garcelon, Mohamad Zaidan, Katy Billot, Friederike Petzold, Hassan Faour, Maxime Douillet, Jean-Michel Rozet, Valérie Cormier-Daire, Tania Attié-Bitach, Stanislas Lyonnet, Sophie Saunier, Anita Burgun
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background There are approximately 8,000 different rare diseases that affect roughly 400 million people worldwide. Many of them suffer from delayed diagnosis. Ciliopathies are rare monogenic disorders characterized by a significant phenotypi
Externí odkaz:
https://doaj.org/article/38d44f5fef63446fa67280a097ada0d1
Autor:
Saunier, Victor
Publikováno v:
Ann. K-Th. 8 (2023) 609-643
We prove a generalization of the fundamental theorem of algebraic K-theory for Verdier-localizing functors by extending the proof for algebraic K-theory of spaces to the realm of stable $\infty$-categories. The formula behaves much better for Karoubi
Externí odkaz:
http://arxiv.org/abs/2209.05818