Zobrazeno 1 - 10
of 11 474
pro vyhledávání: '"A Torralba"'
Fine-tuning is a crucial paradigm for adapting pre-trained large language models to downstream tasks. Recently, methods like Low-Rank Adaptation (LoRA) have been shown to match the performance of fully fine-tuned models on various tasks with an extre
Externí odkaz:
http://arxiv.org/abs/2410.21228
Autor:
Naidu, Rohan P., Matthee, Jorryt, Kramarenko, Ivan, Weibel, Andrea, Brammer, Gabriel, Oesch, Pascal A., Lechner, Peter, Furtak, Lukas J., Di Cesare, Claudia, Torralba, Alberto, Kotiwale, Gauri, Bezanson, Rachel, Bouwens, Rychard J., Chandra, Vedant, Claeyssens, Adélaïde, Danhaive, A. Lola, Frebel, Anna, de Graaff, Anna, Greene, Jenny E., Heintz, Kasper E., Ji, Alexander P., Kashino, Daichi, Katz, Harley, Labbe, Ivo, Leja, Joel, Li, Yijia, Maseda, Michael V., Richard, Johan, Shivaei, Irene, Simcoe, Robert A., Sobral, David, Suess, Katherine A., Tacchella, Sandro, Williams, Christina C.
Dwarf galaxies hold the key to crucial frontiers of astrophysics, however, their faintness renders spectroscopy challenging. Here we present the JWST Cycle 2 survey, All the Little Things (ALT, PID 3516), which is designed to seek late-forming Pop II
Externí odkaz:
http://arxiv.org/abs/2410.01874
Adversarially robust models are locally smooth around each data sample so that small perturbations cannot drastically change model outputs. In modern systems, such smoothness is usually obtained via Adversarial Training, which explicitly enforces mod
Externí odkaz:
http://arxiv.org/abs/2409.20139
Autor:
Chen, Zhenfang, Dong, Shilong, Yi, Kexin, Li, Yunzhu, Ding, Mingyu, Torralba, Antonio, Tenenbaum, Joshua B., Gan, Chuang
Understanding and reasoning about objects' physical properties in the natural world is a fundamental challenge in artificial intelligence. While some properties like colors and shapes can be directly observed, others, such as mass and electric charge
Externí odkaz:
http://arxiv.org/abs/2408.02687
Autor:
Torralba-Torregrosa, Alberto, Renard, Pablo, Spinoso, Daniele, Arnalte-Mur, Pablo, Gurung-López, Siddhartha, Fernández-Soto, Alberto, Gaztañaga, Enrique, Navarro-Gironés, David, Cai, Zheng, Carretero, Jorge, Castander, J. Francisco, Eriksen, Martin, Garcia-Bellido, Juan, Hildebrandt, Hendrik, Hoekstra, Henk, Miquel, Ramon, Sanchez, Eusebio, Tallada-Crespí, Pau, De Vicente, Juan, Fernandez, Enrique
Publikováno v:
A&A 690, A388 (2024)
We present the Lyman-$\alpha$ (Ly$\alpha$) and ultraviolet (UV) luminosity function (LF), in bins of redshift, of quasars selected in the Physics of the Accelerating Universe Survey (PAUS). A sample of 915 objects was selected at $2.7
Externí odkaz:
http://arxiv.org/abs/2407.19020
Data-driven model reduction methods provide a nonintrusive way of constructing computationally efficient surrogates of high-fidelity models for real-time control of soft robots. This work leverages the Lagrangian nature of the model equations to deri
Externí odkaz:
http://arxiv.org/abs/2407.08840
Autor:
Khalatyan, A., Anders, F., Chiappini, C., Queiroz, A. B. A., Nepal, S., Ponte, M. dal, Jordi, C., Guiglion, G., Valentini, M., Elipe, G. Torralba, Steinmetz, M., Pantaleoni-González, M., Malhotra, S., Jiménez-Arranz, Ó., Enke, H., Casamiquela, L., Ardèvol, J.
In this paper, we explore the feasibility of using machine learning regression as a method of extracting basic stellar parameters and line-of-sight extinctions from spectro-photometric data. We built a stable gradient-boosted random-forest regressor
Externí odkaz:
http://arxiv.org/abs/2407.06963
Publikováno v:
J. Mater. Res. Technol. 31 2024 109 116
High entropy alloys (HEAs) represent a novel frontier in metallurgical advancements, offering exceptional mechanical properties owing to their unique multicomponent nature. This study explores a novel strategy utilising commodity powders - Ni625, Inv
Externí odkaz:
http://arxiv.org/abs/2407.03143
Autor:
Ren, Jiawei, Xie, Kevin, Mirzaei, Ashkan, Liang, Hanxue, Zeng, Xiaohui, Kreis, Karsten, Liu, Ziwei, Torralba, Antonio, Fidler, Sanja, Kim, Seung Wook, Ling, Huan
We present L4GM, the first 4D Large Reconstruction Model that produces animated objects from a single-view video input -- in a single feed-forward pass that takes only a second. Key to our success is a novel dataset of multiview videos containing cur
Externí odkaz:
http://arxiv.org/abs/2406.10324
Autor:
C Garcia-Terol, I Perez-Pinedo, R Heras-Trejo, R Gonzalez, L Gimenez, B Carreras, M Brito, A Torralba, P Ricciardeli, M Martinez-Redondo, M De Gracia
Publikováno v:
Psicosomática y Psiquiatría, Iss 17 (2021)
Externí odkaz:
https://doaj.org/article/41e8f0db200d4e23ab40232033a2a19e
