2k citations
- Maxwell Institute for Mathematical SciencesGB436 papers
- University of EdinburghGB146 papers
- Centre National de la Recherche ScientifiqueFR75 papers
- University of OxfordGB65 papers
- University of GlasgowGB63 papers
- Imperial College LondonGB56 papers
- Heriot-Watt University MalaysiaMY51 papers
- Scottish Universities Physics AllianceGB50 papers
- University College LondonGB49 papers
- Max Planck Institute for the Science of LightDE37 papers
- University of GothenburgSE37 papers
- University of StrathclydeGB36 papers
1,841 papers
Stellar interferometry with a K-band integrated optics beam combiner instrument at the CHARA Array - I. First on-sky fringes for CHARIOT
Aline N. Dinkelaker, Kévin Barjot, Nic Scott +8
We present the instrument description and the first on-sky observations for the new CHara ARray Integrated Optics Testbench (CHARIOT) at the CHARA Array. CHARIOT is a 2-telescope p…
Semi-discrete convex order and Laguerre tessellation fitting
David P. Bourne, Thomas Gallouët, Quentin Mérigot +1
Laguerre tessellations offer an efficient way to parameterize a large class of convex partitions of Euclidean space using only a set of points and scalar weights. For this reason,…
TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning
Xiaosong Han, Ke Chen, Xindi Dai +7
In real-world deployment, LLMs are often adapted continually across tasks to keep LLMs up-to-date in production, where new fine-tuning should preserve previously learned skills. Ho…
Advancing Graph Few-Shot Learning via In-Context Learning
Renchu Guan, Yajun Wang, Chunli Guo +5
Graph few-shot learning, which aims to classify nodes from novel classes with only a few labeled examples, is a widely studied problem in graph learning. However, existing methods…
Modularity of Feynman Integrals and Factorization of Appell F2 Systems
Murad Alim, Filippo La Mantia
Certain Feynman integrals can be expressed as periods of differential forms on Calabi--Yau manifolds. We provide a mathematical proof of a result of Duhr and Maggio on the modulari…
AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow
Jiale Liu, Nanzhe Wang
High-fidelity numerical simulation of subsurface flow is computationally intensive, especially for many-query tasks such as uncertainty quantification and data assimilation. Deep l…