Zobrazeno 1 - 10
of 2 668
pro vyhledávání: '"GONTHIER, P"'
Object detection in art is a valuable tool for the digital humanities, as it allows for faster identification of objects in artistic and historical images compared to humans. However, annotating such images poses significant challenges due to the nee
Externí odkaz:
http://arxiv.org/abs/2412.06286
Autor:
Kunitsa, Alexander, Bellonzi, Nicole, Guo, Shangjie, Gonthier, Jérôme F., Buda, Corneliu, Abuan, Clena M., Romero, Jhonathan
This study explores hardware implementation of Robust Amplitude Estimation (RAE) on IBM quantum devices, demonstrating its application in quantum chemistry for one- and two-qubit Hamiltonian systems. Known for potentially offering quadratic speedups
Externí odkaz:
http://arxiv.org/abs/2410.00686
Autor:
Pauloski, J. Gregory, Hayot-Sasson, Valerie, Gonthier, Maxime, Hudson, Nathaniel, Pan, Haochen, Zhou, Sicheng, Foster, Ian, Chard, Kyle
Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tasks into a single, unified application designed to achieve a computatio
Externí odkaz:
http://arxiv.org/abs/2408.07236
Autor:
Pan, Haochen, Chard, Ryan, Zhou, Sicheng, Kamatar, Alok, Vescovi, Rafael, Hayot-Sasson, Valérie, Bauer, André, Gonthier, Maxime, Chard, Kyle, Foster, Ian
Scientific research increasingly relies on distributed computational resources, storage systems, networks, and instruments, ranging from HPC and cloud systems to edge devices. Event-driven architecture (EDA) benefits applications targeting distribute
Externí odkaz:
http://arxiv.org/abs/2407.11432
Autor:
Ollitrault, Pauline J., Cortes, Cristian L., Gonthier, Jerome F., Parrish, Robert M., Rocca, Dario, Anselmetti, Gian-Luca, Degroote, Matthias, Moll, Nikolaj, Santagati, Raffaele, Streif, Michael
The quantum phase estimation algorithm stands as the primary method for determining the ground state energy of a molecular electronic Hamiltonian on a quantum computer. In this context, the ability to initialize a classically tractable state that has
Externí odkaz:
http://arxiv.org/abs/2404.08565
Publikováno v:
ECCV 2024
The diversity and complementarity of sensors available for Earth Observations (EO) calls for developing bespoke self-supervised multimodal learning approaches. However, current multimodal EO datasets and models typically focus on a single data type,
Externí odkaz:
http://arxiv.org/abs/2404.08351
Autor:
Wu, Sidi, Chen, Yizi, Mermet, Samuel, Hurni, Lorenz, Schindler, Konrad, Gonthier, Nicolas, Landrieu, Loic
Most image-to-image translation models postulate that a unique correspondence exists between the semantic classes of the source and target domains. However, this assumption does not always hold in real-world scenarios due to divergent distributions,
Externí odkaz:
http://arxiv.org/abs/2403.20142
Autor:
Cortes, Cristian L., Rocca, Dario, Gonthier, Jerome, Ollitrault, Pauline J., Parrish, Robert M., Anselmetti, Gian-Luca R., Degroote, Matthias, Moll, Nikolaj, Santagati, Raffaele, Streif, Michael
The computational cost of quantum algorithms for physics and chemistry is closely linked to the spectrum of the Hamiltonian, a property that manifests in the necessary rescaling of its eigenvalues. The typical approach of using the 1-norm as an upper
Externí odkaz:
http://arxiv.org/abs/2403.04737
Autor:
Rocca, Dario, Cortes, Cristian L., Gonthier, Jerome, Ollitrault, Pauline J., Parrish, Robert M., Anselmetti, Gian-Luca, Degroote, Matthias, Moll, Nikolaj, Santagati, Raffaele, Streif, Michael
Publikováno v:
J. Chem. Theory Comput. 2024, 20, 11, 4639-4653
Quantum phase estimation based on qubitization is the state-of-the-art fault-tolerant quantum algorithm for computing ground-state energies in chemical applications. In this context, the 1-norm of the Hamiltonian plays a fundamental role in determini
Externí odkaz:
http://arxiv.org/abs/2403.03502
Autor:
Garioud, Anatol, Gonthier, Nicolas, Landrieu, Loic, De Wit, Apolline, Valette, Marion, Poupée, Marc, Giordano, Sébastien, Wattrelos, Boris
We introduce the French Land cover from Aerospace ImageRy (FLAIR), an extensive dataset from the French National Institute of Geographical and Forest Information (IGN) that provides a unique and rich resource for large-scale geospatial analysis. FLAI
Externí odkaz:
http://arxiv.org/abs/2310.13336