Zobrazeno 1 - 10
of 6 449
pro vyhledávání: '"Ashesh A"'
Autor:
Mahajan, Kushal Kumar
Publikováno v:
Biographical Memoirs of Fellows of the Royal Society; December 2024, Vol. 77 Issue: 1 p285-300, 16p
Large language models (LLMs) are being used in economics research to form predictions, label text, simulate human responses, generate hypotheses, and even produce data for times and places where such data don't exist. While these uses are creative, a
Externí odkaz:
http://arxiv.org/abs/2412.07031
Physics-informed neural networks (PINNs) commonly address ill-posed inverse problems by uncovering unknown physics. This study presents a novel unsupervised learning framework that identifies spatial subdomains with specific governing physics. It use
Externí odkaz:
http://arxiv.org/abs/2412.06842
What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learning
Differentiable Programming for scientific machine learning (SciML) has recently seen considerable interest and success, as it directly embeds neural networks inside PDEs, often called as NeuralPDEs, derived from first principle physics. Therefore, th
Externí odkaz:
http://arxiv.org/abs/2411.15101
While traditional program evaluations typically rely on surveys to measure outcomes, certain economic outcomes such as living standards or environmental quality may be infeasible or costly to collect. As a result, recent empirical work estimates trea
Externí odkaz:
http://arxiv.org/abs/2411.10959
Autor:
Sun, Y. Qiang, Hassanzadeh, Pedram, Zand, Mohsen, Chattopadhyay, Ashesh, Weare, Jonathan, Abbot, Dorian S.
Predicting gray swan weather extremes, which are possible but so rare that they are absent from the training dataset, is a major concern for AI weather/climate models. An important open question is whether AI models can extrapolate from weaker weathe
Externí odkaz:
http://arxiv.org/abs/2410.14932
Gas volume density is one of the critical parameters, along with dispersions in magnetic field position angles and non-thermal gas motions, for estimating the magnetic field strength using the Davis-Chandrasekhar-Fermi (DCF) relation or through its m
Externí odkaz:
http://arxiv.org/abs/2410.04859
Predicting the long-term behavior of chaotic systems remains a formidable challenge due to their extreme sensitivity to initial conditions and the inherent limitations of traditional data-driven modeling approaches. This paper introduces a novel fram
Externí odkaz:
http://arxiv.org/abs/2410.05572
We present a solution for the Green's function for the general case of a helical wormlike chain with twist-bend coupling, and demonstrate the applicability of our solution for evaluating general structural and mechanical chain properties. We find tha
Externí odkaz:
http://arxiv.org/abs/2408.08954
Microscopy is routinely used to image biological structures of interest. Due to imaging constraints, acquired images, also called as micrographs, are typically low-SNR and contain noise. Over the last few years, regression-based tasks like unsupervis
Externí odkaz:
http://arxiv.org/abs/2408.08747