Zobrazeno 1 - 10
of 20 021
pro vyhledávání: '"P. CARON"'
A significant challenge for autonomous cyber defence is ensuring a defensive agent's ability to generalise across diverse network topologies and configurations. This capability is necessary for agents to remain effective when deployed in dynamically
Externí odkaz:
http://arxiv.org/abs/2410.17647
Contact estimation is a key ability for limbed robots, where making and breaking contacts has a direct impact on state estimation and balance control. Existing approaches typically rely on gate-cycle priors or designated contact sensors. We design a
Externí odkaz:
http://arxiv.org/abs/2410.12345
Merging in a Bottle: Differentiable Adaptive Merging (DAM) and the Path from Averaging to Automation
Autor:
Gauthier-Caron, Thomas, Siriwardhana, Shamane, Stein, Elliot, Ehghaghi, Malikeh, Goddard, Charles, McQuade, Mark, Solawetz, Jacob, Labonne, Maxime
By merging models, AI systems can combine the distinct strengths of separate language models, achieving a balance between multiple capabilities without requiring substantial retraining. However, the integration process can be intricate due to differe
Externí odkaz:
http://arxiv.org/abs/2410.08371
Overseas military personnel often face significant challenges in participating in elections due to the slow pace of traditional mail systems, which can result in ballots missing crucial deadlines. While internet-based voting offers a faster alternati
Externí odkaz:
http://arxiv.org/abs/2410.06705
Autor:
Arodi, Akshatha, Luck, Margaux, Bedwani, Jean-Luc, Zaimi, Aldo, Li, Ge, Pouliot, Nicolas, Beaudry, Julien, Caron, Gaétan Marceau
Machine learning models are increasingly being deployed in real-world contexts. However, systematic studies on their transferability to specific and critical applications are underrepresented in the research literature. An important example is visual
Externí odkaz:
http://arxiv.org/abs/2409.20353
With the advent of billion-parameter foundation models, efficient fine-tuning has become increasingly important for the adaptation of models to downstream tasks. However, especially in computer vision, it can be hard to achieve good performance when
Externí odkaz:
http://arxiv.org/abs/2409.07577
Data-driven methods demonstrate considerable potential for accelerating the inherently expensive computational fluid dynamics (CFD) solvers. Nevertheless, pure machine-learning surrogate models face challenges in ensuring physical consistency and sca
Externí odkaz:
http://arxiv.org/abs/2409.07175
Autor:
Caron-Huot, Simon, Li, Yue-Zhou
We analyze the one-loop effects of massive fields on 2-to-2 scattering processes involving gravitons. It has been suggested that in the presence of gravity, any local effective field theory description must break down at the "species scale". We first
Externí odkaz:
http://arxiv.org/abs/2408.06440
Autor:
Caron, Sascha, Dobreva, Nadezhda, Sánchez, Antonio Ferrer, Martín-Guerrero, José D., Odyurt, Uraz, Bazan, Roberto Ruiz de Austri, Wolffs, Zef, Zhao, Yue
High-Energy Physics experiments are facing a multi-fold data increase with every new iteration. This is certainly the case for the upcoming High-Luminosity LHC upgrade. Such increased data processing requirements forces revisions to almost every step
Externí odkaz:
http://arxiv.org/abs/2407.07179
Autor:
Husain, Syed Zahid, Separovic, Leo, Caron, Jean-François, Aider, Rabah, Buehner, Mark, Chamberland, Stéphane, Lapalme, Ervig, McTaggart-Cowan, Ron, Subich, Christopher, Vaillancourt, Paul A., Yang, Jing, Zadra, Ayrton
Operational meteorological forecasting has long relied on physics-based numerical weather prediction (NWP) models. Recently, this landscape is facing disruption by the advent of data-driven artificial intelligence (AI)-based weather models, which off
Externí odkaz:
http://arxiv.org/abs/2407.06100