Zobrazeno 1 - 10
of 148 065
pro vyhledávání: '"A. A. Hamed"'
Autor:
Abbasi, Ali, Imani, Shima, An, Chenyang, Mahalingam, Gayathri, Shrivastava, Harsh, Diesendruck, Maurice, Pirsiavash, Hamed, Sharma, Pramod, Kolouri, Soheil
With the rapid scaling of neural networks, data storage and communication demands have intensified. Dataset distillation has emerged as a promising solution, condensing information from extensive datasets into a compact set of synthetic samples by so
Externí odkaz:
http://arxiv.org/abs/2412.04668
Autor:
Moniri, Behrad, Hassani, Hamed
In this paper we study the asymptotics of linear regression in settings with non-Gaussian covariates where the covariates exhibit a linear dependency structure, departing from the standard assumption of independence. We model the covariates using sto
Externí odkaz:
http://arxiv.org/abs/2412.03702
Autor:
Szwarcman, Daniela, Roy, Sujit, Fraccaro, Paolo, Gíslason, Þorsteinn Elí, Blumenstiel, Benedikt, Ghosal, Rinki, de Oliveira, Pedro Henrique, Almeida, Joao Lucas de Sousa, Sedona, Rocco, Kang, Yanghui, Chakraborty, Srija, Wang, Sizhe, Kumar, Ankur, Truong, Myscon, Godwin, Denys, Lee, Hyunho, Hsu, Chia-Yu, Asanjan, Ata Akbari, Mujeci, Besart, Keenan, Trevor, Arevalo, Paulo, Li, Wenwen, Alemohammad, Hamed, Olofsson, Pontus, Hain, Christopher, Kennedy, Robert, Zadrozny, Bianca, Cavallaro, Gabriele, Watson, Campbell, Maskey, Manil, Ramachandran, Rahul, Moreno, Juan Bernabe
This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA's Harmonized Landsat and Sentinel-2 data
Externí odkaz:
http://arxiv.org/abs/2412.02732
Autor:
Sawant, P., Nanni, A., Romano, M., Donevski, D., Bruzual, G., Ysard, N., Lemaux, B. C., Inami, H., Calura, F., Pozzi, F., Małek, K., Junais, Boquien, M., Faisst, A. L., Hamed, M., Ginolfi, M., Zamorani, G., Lorenzon, G., Molina, J., Bardelli, S., Ibar, E., Vergani, D., Di Cesare, C., Béthermin, M., Burgarella, D., Cassata, P., Dessauges-Zavadsky, M., D'Onghia, E., Dubois, Y., Magdis, G. E., Mendez-Hernandez, H.
Recent observations reveal a rapid dust build-up in high-redshift galaxies (z > 4), challenging current models of galaxy formation. While our understanding of dust production and destruction in the interstellar medium (ISM) is advancing, probing bary
Externí odkaz:
http://arxiv.org/abs/2412.02505
In the fast-evolving field of information retrieval (IR), the integration of generative AI technologies such as large language models (LLMs) is transforming how users search for and interact with information. Recognizing this paradigm shift at the in
Externí odkaz:
http://arxiv.org/abs/2412.02043
Autor:
Haggi, Hamed, Sun, Wei
As the adoption of distributed energy resources grows, power systems are becoming increasingly complex and vulnerable to disruptions, such as natural disasters and cyber-physical threats. Peer-to-peer (P2P) energy markets offer a practical solution t
Externí odkaz:
http://arxiv.org/abs/2412.00873
Autor:
Tadesse, Girmaw Abebe, Robinson, Caleb, Mwangi, Charles, Maina, Esther, Nyakundi, Joshua, Marotti, Luana, Hacheme, Gilles Quentin, Alemohammad, Hamed, Dodhia, Rahul, Ferres, Juan M. Lavista
In 2023, 58.0% of the African population experienced moderate to severe food insecurity, with 21.6% facing severe food insecurity. Land-use and land-cover maps provide crucial insights for addressing food insecurity by improving agricultural efforts,
Externí odkaz:
http://arxiv.org/abs/2412.00777
Autor:
Haggi, Hamed, Fenton, James M.
The decreasing costs of photovoltaic (PV) systems and battery storage, alongside the rapid rise of electric vehicles (EVs), present a unique opportunity to revolutionize energy use in apartment complexes. Generating electricity via PV and batteries i
Externí odkaz:
http://arxiv.org/abs/2412.00875
Autor:
Haggi, Hamed, Fenton, James M.
Recent advancements, net-zero emission policies, along with declining costs of renewable energy, battery storage, and electric vehicles (EVs), are accelerating the transition toward cleaner, more resilient energy systems. This paper conducts a compre
Externí odkaz:
http://arxiv.org/abs/2412.00874
The automatic detection of pedestrian heads in crowded environments is essential for crowd analysis and management tasks, particularly in high-risk settings such as railway platforms and event entrances. These environments, characterized by dense cro
Externí odkaz:
http://arxiv.org/abs/2411.18164