Zobrazeno 1 - 10
of 1 009
pro vyhledávání: '"Araújo, João P."'
Autor:
Moreira, Ricardo P., da Silva, E. Lora, Oliveira, Gonçalo N. P., Rocha-Rodrigues, Pedro, Stroppa, Alessandro, Colin, Claire V., Darie, Céline, Correia, João G., Assali, Lucy V. C., Petrilli, Helena M., Lopes, Armandina M. L., Araújo, João P.
The structural and electronic properties of the CaMnGe$_2$O$_6$ and SrMnGe$_2$O$_6$ clinopyroxene systems have been investigated by means of perturbed angular correlation (PAC) measurements, performed at ISOLDE, combined with $ab-initio$ electronic s
Externí odkaz:
http://arxiv.org/abs/2407.21749
Deep reinforcement learning (deep RL) has achieved tremendous success on various domains through a combination of algorithmic design and careful selection of hyper-parameters. Algorithmic improvements are often the result of iterative enhancements bu
Externí odkaz:
http://arxiv.org/abs/2406.17523
Autor:
Barbero, Federico, Banino, Andrea, Kapturowski, Steven, Kumaran, Dharshan, Araújo, João G. M., Vitvitskyi, Alex, Pascanu, Razvan, Veličković, Petar
We study how information propagates in decoder-only Transformers, which are the architectural backbone of most existing frontier large language models (LLMs). We rely on a theoretical signal propagation analysis -- specifically, we analyse the repres
Externí odkaz:
http://arxiv.org/abs/2406.04267
Autor:
Gavranović, Bruno, Lessard, Paul, Dudzik, Andrew, von Glehn, Tamara, Araújo, João G. M., Veličković, Petar
We present our position on the elusive quest for a general-purpose framework for specifying and studying deep learning architectures. Our opinion is that the key attempts made so far lack a coherent bridge between specifying constraints which models
Externí odkaz:
http://arxiv.org/abs/2402.15332
Autor:
Huang, Shengyi, Gallouédec, Quentin, Felten, Florian, Raffin, Antonin, Dossa, Rousslan Fernand Julien, Zhao, Yanxiao, Sullivan, Ryan, Makoviychuk, Viktor, Makoviichuk, Denys, Danesh, Mohamad H., Roumégous, Cyril, Weng, Jiayi, Chen, Chufan, Rahman, Md Masudur, Araújo, João G. M., Quan, Guorui, Tan, Daniel, Klein, Timo, Charakorn, Rujikorn, Towers, Mark, Berthelot, Yann, Mehta, Kinal, Chakraborty, Dipam, KG, Arjun, Charraut, Valentin, Ye, Chang, Liu, Zichen, Alegre, Lucas N., Nikulin, Alexander, Hu, Xiao, Liu, Tianlin, Choi, Jongwook, Yi, Brent
In many Reinforcement Learning (RL) papers, learning curves are useful indicators to measure the effectiveness of RL algorithms. However, the complete raw data of the learning curves are rarely available. As a result, it is usually necessary to repro
Externí odkaz:
http://arxiv.org/abs/2402.03046
Time-lapse images carry out important information about dynamic changes in Earth's interior which can be inferred using different Full Waveform Inversion (FWI) schemes. The estimation process is performed by manipulating more than one seismic dataset
Externí odkaz:
http://arxiv.org/abs/2311.02999
Autor:
Araujo, Joao Pedro, Li, Jiaman, Vetrivel, Karthik, Agarwal, Rishi, Gopinath, Deepak, Wu, Jiajun, Clegg, Alexander, Liu, C. Karen
Synthesizing 3D human motion in a contextual, ecological environment is important for simulating realistic activities people perform in the real world. However, conventional optics-based motion capture systems are not suited for simultaneously captur
Externí odkaz:
http://arxiv.org/abs/2303.17912
Autor:
Araújo, João, Bentz, Wolfram, Kinyon, Michael, Konieczny, Janusz, Malheiro, António, Mercier, Valentin
The conjugacy relation plays an important role in group theory. If $a$ and $b$ are elements of a group~$G$, $a$ is conjugate to $b$ if $g^{-1}ag=b$ for some $g\in G$. Group conjugacy extends to inverse semigroups in a natural way: for $a$ and $b$ in
Externí odkaz:
http://arxiv.org/abs/2301.04252
Autor:
Wang, Kuan-Chieh, Weng, Zhenzhen, Xenochristou, Maria, Araujo, Joao Pedro, Gu, Jeffrey, Liu, C. Karen, Yeung, Serena
The task of reconstructing 3D human motion has wideranging applications. The gold standard Motion capture (MoCap) systems are accurate but inaccessible to the general public due to their cost, hardware and space constraints. In contrast, monocular hu
Externí odkaz:
http://arxiv.org/abs/2212.13660
Full-Waveform Inversion (FWI) is a high-resolution technique used in geophysics to evaluate the physical parameters and construct subsurface models in a noisy and limited data scenario. The ill-posed nature of the FWI turns this a challenging problem
Externí odkaz:
http://arxiv.org/abs/2206.00622