Zobrazeno 1 - 10
of 23 839
pro vyhledávání: '"A. Bhattarai"'
We present a methodology to generate low-latency, high spatio-temporal resolution thermospheric density estimates using publicly available Low Earth Orbit (LEO) spacecraft ephemerides. This provides a means of generating density estimates that can be
Externí odkaz:
http://arxiv.org/abs/2408.16805
Autor:
Huang, Baoru, Vo, Tuan, Kongtongvattana, Chayun, Dagnino, Giulio, Kundrat, Dennis, Chi, Wenqiang, Abdelaziz, Mohamed, Kwok, Trevor, Jianu, Tudor, Do, Tuong, Le, Hieu, Nguyen, Minh, Nguyen, Hoan, Tjiputra, Erman, Tran, Quang, Xie, Jianyang, Meng, Yanda, Bhattarai, Binod, Tan, Zhaorui, Liu, Hongbin, Gan, Hong Seng, Wang, Wei, Yang, Xi, Wang, Qiufeng, Su, Jionglong, Huang, Kaizhu, Stefanidis, Angelos, Guo, Min, Du, Bo, Tao, Rong, Vu, Minh, Zheng, Guoyan, Zheng, Yalin, Vasconcelos, Francisco, Stoyanov, Danail, Elson, Daniel, Baena, Ferdinando Rodriguez y, Nguyen, Anh
Real-time visual feedback from catheterization analysis is crucial for enhancing surgical safety and efficiency during endovascular interventions. However, existing datasets are often limited to specific tasks, small scale, and lack the comprehensive
Externí odkaz:
http://arxiv.org/abs/2408.13126
Autor:
Vu, Minh, Nebgen, Ben, Skau, Erik, Zollicoffer, Geigh, Castorena, Juan, Rasmussen, Kim, Alexandrov, Boian, Bhattarai, Manish
As Machine Learning (ML) applications rapidly grow, concerns about adversarial attacks compromising their reliability have gained significant attention. One unsupervised ML method known for its resilience to such attacks is Non-negative Matrix Factor
Externí odkaz:
http://arxiv.org/abs/2408.03909
Autor:
Sapkota, Dixant Bikal, Neupane, Puskar, Shiwakoti, Bivek, Baral, Saugat, Bhattarai, Panas, Gautam, Basanta Kumar
This paper explores the analysis and implementation of the Virtual Oscillator Control (VOC) strategy for inverters aiming to enhance stability amidst the ever-increasing generation of renewable energy sources like solar PV. Key objectives include imp
Externí odkaz:
http://arxiv.org/abs/2408.02468
Autor:
Bhattarai, Binod, Loebman, Sarah R., Ness, Melissa K., Wetzel, Andrew, Cunningham, Emily C., Parul, Hanna, Wiggins, Alessa Ibrahim
Open star clusters are the essential building blocks of the Galactic disk; "strong chemical tagging" - the premise that all star clusters can be reconstructed given chemistry information alone - is a driving force behind many current and upcoming lar
Externí odkaz:
http://arxiv.org/abs/2408.02228
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing (NLP) tasks, such as question-answering, sentiment analysis, text summarization, and machine translation. Howev
Externí odkaz:
http://arxiv.org/abs/2408.01008
Autor:
Bhattarai, Manish, Santos, Javier E., Jones, Shawn, Biswas, Ayan, Alexandrov, Boian, O'Malley, Daniel
The advent of large language models (LLMs) has significantly advanced the field of code translation, enabling automated translation between programming languages. However, these models often struggle with complex translation tasks due to inadequate c
Externí odkaz:
http://arxiv.org/abs/2407.19619
Autor:
Wanna, Selma, Barron, Ryan, Solovyev, Nick, Eren, Maksim E., Bhattarai, Manish, Rasmussen, Kim, Alexandrov, Boian S.
Topic modeling is a technique for organizing and extracting themes from large collections of unstructured text. Non-negative matrix factorization (NMF) is a common unsupervised approach that decomposes a term frequency-inverse document frequency (TF-
Externí odkaz:
http://arxiv.org/abs/2407.19616
Autor:
Barron, Ryan, Eren, Maksim E., Bhattarai, Manish, Boureima, Ismael, Matuszek, Cynthia, Alexandrov, Boian S.
In several Machine Learning (ML) clustering and dimensionality reduction approaches, such as non-negative matrix factorization (NMF), RESCAL, and K-Means clustering, users must select a hyper-parameter k to define the number of clusters or components
Externí odkaz:
http://arxiv.org/abs/2407.19125
Autor:
Pokhrel, Sandesh, Bhandari, Sanjay, Vazquez, Eduard, Lambrou, Tryphon, Gyawali, Prashnna, Bhattarai, Binod
Deep learning has significantly advanced the field of gastrointestinal vision, enhancing disease diagnosis capabilities. One major challenge in automating diagnosis within gastrointestinal settings is the detection of abnormal cases in endoscopic ima
Externí odkaz:
http://arxiv.org/abs/2407.14024