Zobrazeno 1 - 10
of 3 891
pro vyhledávání: '"P. Carron"'
Predictive Spliner: Data-Driven Overtaking in Autonomous Racing Using Opponent Trajectory Prediction
Autor:
Baumann, Nicolas, Ghignone, Edoardo, Hu, Cheng, Hildisch, Benedict, Hämmerle, Tino, Bettoni, Alessandro, Carron, Andrea, Xie, Lei, Magno, Michele
Head-to-head racing against opponents is a challenging and emerging topic in the domain of autonomous racing. We propose Predictive Spliner, a data-driven overtaking planner that learns the behavior of opponents through Gaussian Process (GP) regressi
Externí odkaz:
http://arxiv.org/abs/2410.04868
We propose a novel data-driven stochastic model predictive control framework for uncertain linear systems with noisy output measurements. Our approach leverages multi-step predictors to efficiently propagate uncertainty, ensuring chance constraint sa
Externí odkaz:
http://arxiv.org/abs/2409.10405
Autor:
Saha, Samanta, Copi, Craig J., Starkman, Glenn D., Anselmi, Stefano, Duque, Javier Carrón, Barandiaran, Mikel Martin, Akrami, Yashar, Cornet-Gomez, Fernando, Jaffe, Andrew H., Kosowsky, Arthur, Mihaylov, Deyan P., Pereira, Thiago S., Samandar, Amirhossein, Tamosiunas, Andrius
Cosmic microwave background (CMB) temperature and polarization observations indicate that in the best-fit $\Lambda$ Cold Dark Matter model of the Universe, the local geometry is consistent with at most a small amount of positive or negative curvature
Externí odkaz:
http://arxiv.org/abs/2409.02226
Optical training of large-scale Transformers and deep neural networks with direct feedback alignment
Autor:
Wang, Ziao, Müller, Kilian, Filipovich, Matthew, Launay, Julien, Ohana, Ruben, Pariente, Gustave, Mokaadi, Safa, Brossollet, Charles, Moreau, Fabien, Cappelli, Alessandro, Poli, Iacopo, Carron, Igor, Daudet, Laurent, Krzakala, Florent, Gigan, Sylvain
Modern machine learning relies nearly exclusively on dedicated electronic hardware accelerators. Photonic approaches, with low consumption and high operation speed, are increasingly considered for inference but, to date, remain mostly limited to rela
Externí odkaz:
http://arxiv.org/abs/2409.12965
When it comes to the safety of cosmetic products, compliance with regulatory standards is crucialto guarantee consumer protection against the risks of skin irritation. Toxicologists must thereforebe fully conversant with all risks. This applies not o
Externí odkaz:
http://arxiv.org/abs/2408.12184
We introduce data to predictive control, D2PC, a framework to facilitate the design of robust and predictive controllers from data. The proposed framework is designed for discrete-time stochastic linear systems with output measurements and provides a
Externí odkaz:
http://arxiv.org/abs/2407.17277
Autor:
Samandar, Amirhossein, Duque, Javier Carrón, Copi, Craig J., Barandiaran, Mikel Martin, Mihaylov, Deyan P., Pereira, Thiago S., Starkman, Glenn D., Akrami, Yashar, Anselmi, Stefano, Cornet-Gomez, Fernando, Eskilt, Johannes R., Jaffe, Andrew H., Kosowsky, Arthur, Tamosiunas, Andrius
The standard cosmological model, which assumes statistical isotropy and parity invariance, predicts the absence of correlations between even-parity and odd-parity observables of the cosmic microwave background (CMB). Contrary to these predictions, la
Externí odkaz:
http://arxiv.org/abs/2407.09400
The gravitational lensing signal from the Cosmic Microwave Background is highly valuable to constrain the growth of the structures in the Universe in a clean and robust manner over a wide range of redshifts. One of the theoretical systematics for len
Externí odkaz:
http://arxiv.org/abs/2407.00228
Curl lensing, also known as lensing field-rotation or shear B-modes, is a distinct post-Born observable caused by two lensing deflections at different redshifts (lens-lens coupling). For the Cosmic Microwave Background (CMB), the field-rotation is ap
Externí odkaz:
http://arxiv.org/abs/2406.19998
Autor:
Belkner, Sebastian, Duivenvoorden, Adriaan J., Carron, Julien, Schaeffer, Nathanael, Reinecke, Martin
We present $\texttt{cunusht}$, a general-purpose Python package that wraps a highly efficient CUDA implementation of the nonuniform spin-$0$ spherical harmonic transform. The method is applicable to arbitrary pixelization schemes, including schemes c
Externí odkaz:
http://arxiv.org/abs/2406.14542