Zobrazeno 1 - 10
of 3 535
pro vyhledávání: '"Abhirup Are"'
Autor:
Li, Lei, Smith, Hannah, Lyu, Yilin, Camps, Julia, Rodriguez, Blanca, Banerjee, Abhirup, Grau, Vicente
Cardiac digital twins (CDTs) offer personalized \textit{in-silico} cardiac representations for the inference of multi-scale properties tied to cardiac mechanisms. The creation of CDTs requires precise information about the electrode position on the t
Externí odkaz:
http://arxiv.org/abs/2408.13945
Autor:
Chatterjee, Swarna, Pillay, Denisha, Datta, Abhirup, Raja, Ramij, Knowles, Kenda, Rahaman, Majidul, Sikhosana, S. P.
Multiwavelength studies of galaxy clusters are crucial for understanding the complex interconnection of the thermal and non-thermal constituents of these massive structures and uncovering the physical processes involved in their formation and evoluti
Externí odkaz:
http://arxiv.org/abs/2408.09571
The redshifted $21$\,cm signal of neutral hydrogen can be used as a direct probe of the intergalactic medium during Cosmic Dawn\,(CD) and Epoch of Reionization\,(EoR). However, detecting this inherently weak signal has numerous challenges. The major
Externí odkaz:
http://arxiv.org/abs/2407.17573
Cardiovascular diseases (CVDs) are the most common cause of death worldwide. Invasive x-ray coronary angiography (ICA) is one of the most important imaging modalities for the diagnosis of CVDs. ICA typically acquires only two 2D projections, which ma
Externí odkaz:
http://arxiv.org/abs/2407.14616
Understanding the first billion years of the universe requires studying two critical epochs: the Epoch of Reionization (EoR) and Cosmic Dawn (CD). However, due to limited data, the properties of the Intergalactic Medium (IGM) during these periods rem
Externí odkaz:
http://arxiv.org/abs/2406.15832
Federated Learning (FL) enables model development by leveraging data distributed across numerous edge devices without transferring local data to a central server. However, existing FL methods still face challenges when dealing with scarce and label-s
Externí odkaz:
http://arxiv.org/abs/2406.09547
Autor:
Xu, Wentian, Moffat, Matthew, Seale, Thalia, Liang, Ziyun, Wagner, Felix, Whitehouse, Daniel, Menon, David, Newcombe, Virginia, Voets, Natalie, Banerjee, Abhirup, Kamnitsas, Konstantinos
Publikováno v:
Proceedings of Machine Learning Research, MIDL 2024
Models for segmentation of brain lesions in multi-modal MRI are commonly trained for a specific pathology using a single database with a predefined set of MRI modalities, determined by a protocol for the specific disease. This work explores the follo
Externí odkaz:
http://arxiv.org/abs/2405.18511
The observation of gravitational waves from compact binary coalescences is a promising tool to test the validity of general relativity (GR) in a highly dynamical strong-field regime. There are now a variety of tests of GR performed on the observed co
Externí odkaz:
http://arxiv.org/abs/2405.05884
Reinforcement learning (RL) based autonomous driving has emerged as a promising alternative to data-driven imitation learning approaches. However, crafting effective reward functions for RL poses challenges due to the complexity of defining and quant
Externí odkaz:
http://arxiv.org/abs/2403.18965
Heart failure (HF) poses a significant public health challenge, with a rising global mortality rate. Early detection and prevention of HF could significantly reduce its impact. We introduce a novel methodology for predicting HF risk using 12-lead ele
Externí odkaz:
http://arxiv.org/abs/2403.10581