Zobrazeno 1 - 10
of 468
pro vyhledávání: '"Parthipan P"'
Autor:
Parthipan, Raghul, Anand, Mohit, Christensen, Hannah M., Hosking, J. Scott, Wischik, Damon J.
Machine learning (ML) has recently shown significant promise in modelling atmospheric systems, such as the weather. Many of these ML models are autoregressive, and error accumulation in their forecasts is a key problem. However, there is no clear def
Externí odkaz:
http://arxiv.org/abs/2405.14714
Deep neural networks (DNNs) have been used to create models for many complex analysis problems like image recognition and medical diagnosis. DNNs are a popular tool within machine learning due to their ability to model complex patterns and distributi
Externí odkaz:
http://arxiv.org/abs/2405.06859
Atmospheric models used for weather and climate prediction are traditionally formulated in a deterministic manner. In other words, given a particular state of the resolved scale variables, the most likely forcing from the sub-grid scale processes is
Externí odkaz:
http://arxiv.org/abs/2402.09471
Autor:
Siva, Parthipan, Wong, Alexander, Hewston, Patricia, Ioannidis, George, Adachi, Jonathan, Rabinovich, Alexander, Lee, Andrea, Papaioannou, Alexandra
With an aging population, numerous assistive and monitoring technologies are under development to enable older adults to age in place. To facilitate aging in place predicting risk factors such as falls, and hospitalization and providing early interve
Externí odkaz:
http://arxiv.org/abs/2401.01868
We propose the Taylorformer for random processes such as time series. Its two key components are: 1) the LocalTaylor wrapper which adapts Taylor approximations (used in dynamical systems) for use in neural network-based probabilistic models, and 2) t
Externí odkaz:
http://arxiv.org/abs/2305.19141
Autor:
Parthipan, Raghul, Wischik, Damon J.
How can we learn from all available data when training machine-learnt climate models, without incurring any extra cost at simulation time? Typically, the training data comprises coarse-grained high-resolution data. But only keeping this coarse-graine
Externí odkaz:
http://arxiv.org/abs/2210.04001
Autor:
Balakrishnan Muthukumar, Ramanathan Duraimurugan, Punniyakotti Parthipan, Rajaram Rajamohan, Rajakrishnan Rajagopal, Jayaraman Narenkumar, Aruliah Rajasekar, Tabarak Malik
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Crude oil hydrocarbons are considered major environmental pollutants and pose a significant threat to the environment and humans due to having severe carcinogenic and mutagenic effects. Bioremediation is one of the practical and promising te
Externí odkaz:
https://doaj.org/article/959bda9bbfbf4e6a9348c01063bd9ffe
Autor:
V. Thamizharasan, V. Parthipan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract In signal processing applications, the multipliers are essential component of arithmetic functional units in many applications, like digital signal processors, image/video processing, Machine Learning, Cryptography and Arithmetic & Logical u
Externí odkaz:
https://doaj.org/article/13a0ffef678c44869ef1351a40b9dad4
Autor:
Azhagarsamy Satheeshkumar, Ramanathan Duraimurugan, Punniyakotti Parthipan, Kuppusamy Sathishkumar, Mohamad S. AlSalhi, Sandhanasamy Devanesan, Rajaram Rajamohan, Aruliah Rajasekar, Tabarak Malik
Publikováno v:
ACS Omega, Vol 9, Iss 13, Pp 15239-15250 (2024)
Externí odkaz:
https://doaj.org/article/d784dcc9c2a74c0f9f611c66d3c1d867
Publikováno v:
The Indian Journal of Agricultural Sciences, Vol 94, Iss 8 (2024)
The experiment was conducted during 2019–23 at Tamil Nadu Rice Research Institute (Tamil Nadu Agricultural University, Coimbatore), Aduthurai, Tamil Nadu to analyse the effect of conservation tillage methods on bulk density, soil penetration resist
Externí odkaz:
https://doaj.org/article/597bd06ab8cb464988b38f434830f8e7