Zobrazeno 1 - 10
of 9 388
pro vyhledávání: '"A. Garcès"'
Autor:
Garcés, Adrià, Levis, Demian
We present a general framework for incorporating non-reciprocal interactions into the Ising model with Glauber dynamics, without requiring multiple species. We then focus on a model with vision-cone type interactions. We solve it in a fully connected
Externí odkaz:
http://arxiv.org/abs/2411.03544
Autor:
Le, Thanh-Dung, Ha, Vu Nguyen, Nguyen, Ti Ti, Eappen, Geoffrey, Thiruvasagam, Prabhu, Chou, Hong-fu, Tran, Duc-Dung, Garces-Socarras, Luis M., Gonzalez-Rios, Jorge L., Merlano-Duncan, Juan Carlos, Chatzinotas, Symeon
This study presents an innovative dynamic weighting knowledge distillation (KD) framework tailored for efficient Earth observation (EO) image classification (IC) in resource-constrained settings. Utilizing EfficientViT and MobileViT as teacher models
Externí odkaz:
http://arxiv.org/abs/2411.00209
Autor:
Chou, Hong-fu, Ha, Vu Nguyen, Thiruvasagam, Prabhu, Le, Thanh-Dung, Eappen, Geoffrey, Nguyen, Ti Ti, Tran, Duc Dung, Garces-Socarras, Luis M., Merlano-Duncan, Juan Carlos, Chatzinotas, Symeon
Earth observation (EO) systems are essential for mapping, catastrophe monitoring, and resource management, but they have trouble processing and sending large amounts of EO data efficiently, especially for specialized applications like agriculture and
Externí odkaz:
http://arxiv.org/abs/2410.21916
Autor:
Arias, Esteban Garces, Blocher, Hannah, Rodemann, Julian, Li, Meimingwei, Heumann, Christian, Aßenmacher, Matthias
Open-ended text generation has become a prominent task in natural language processing due to the rise of powerful (large) language models. However, evaluating the quality of these models and the employed decoding strategies remains challenging becaus
Externí odkaz:
http://arxiv.org/abs/2410.18653
Autor:
Pydimarry, Sai Abhinav, Khairnar, Shekhar Madhav, Palacios, Sofia Garces, Sankaranarayanan, Ganesh, Hoagland, Darian, Nepomnayshy, Dmitry, Nguyen, Huu Phong
Publikováno v:
RECPAD 2024
In the field of pattern recognition, achieving high accuracy is essential. While training a model to recognize different complex images, it is vital to fine-tune the model to achieve the highest accuracy possible. One strategy for fine-tuning a model
Externí odkaz:
http://arxiv.org/abs/2410.06879
Decoding strategies for large language models (LLMs) are a critical but often underexplored aspect of text generation tasks. Since LLMs produce probability distributions over the entire vocabulary, various decoding methods have been developed to tran
Externí odkaz:
http://arxiv.org/abs/2410.06097
Autor:
Chou, Hong-fu, Ha, Vu Nguyen, Thiruvasagam, Prabhu, Le, Thanh-Dung, Eappen, Geoffrey, Nguyen, Ti Ti, Garces-Socarras, Luis M., Gonzalez-Rios, Jorge L., Merlano-Duncan, Juan Carlos, Chatzinotas, Symeon
Earth Observation (EO) systems are crucial for cartography, disaster surveillance, and resource administration. Nonetheless, they encounter considerable obstacles in the processing and transmission of extensive data, especially in specialized domains
Externí odkaz:
http://arxiv.org/abs/2409.15246
Autor:
Le, Thanh-Dung, Ha, Vu Nguyen, Nguyen, Ti Ti, Eappen, Geoffrey, Thiruvasagam, Prabhu, Garces-Socarras, Luis M., Chou, Hong-fu, Gonzalez-Rios, Jorge L., Merlano-Duncan, Juan Carlos, Chatzinotas, Symeon
This study focuses on identifying the most effective pre-trained model for land use classification in onboard satellite processing, emphasizing achieving high accuracy, computational efficiency, and robustness against noisy data conditions commonly e
Externí odkaz:
http://arxiv.org/abs/2409.03901
Autor:
Wang, Kangwang, Wu, Mingjie, Yu, Peifeng, Garces, Hector F., Liang, Ying, Li, Longfu, Zeng, Lingyong, Li, Kuan, Zhang, Chao, Yan, Kai, Luo, Huixia
Publikováno v:
Applied Catalysis B: Environment and Energy,2024,352,124058
Despite ongoing research, the rational design of nontrivial topological semimetal surface states for the selective photocatalytic CO$_2$ conversion into valuable products remains full of challenges. Herein, we present the synthesis of 1T-OsCoTe$_2$ f
Externí odkaz:
http://arxiv.org/abs/2408.11369
Autor:
Arias, Esteban Garces, Rodemann, Julian, Li, Meimingwei, Heumann, Christian, Aßenmacher, Matthias
Decoding from the output distributions of large language models to produce high-quality text is a complex challenge in language modeling. Various approaches, such as beam search, sampling with temperature, $k-$sampling, nucleus $p-$sampling, typical
Externí odkaz:
http://arxiv.org/abs/2407.18698