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Fitting a graphical model to a collection of random variables given sample observations is a challenging task if the observed variables are influenced by latent variables, which can induce significant confounding statistical dependencies…

Machine Learning · Statistics 2020-10-20 Armeen Taeb , Parikshit Shah , Venkat Chandrasekaran

Kinetically-constrained models are lattice-gas models that are used for describing glassy systems. By construction, their equilibrium state is trivial and there are no equal-time correlations between the occupancy of different sites. We…

Statistical Mechanics · Physics 2017-03-01 Eial Teomy , Yair Shokef

Power law cumulative frequency $(P)$ vs. event size $(l)$ distributions $P(\geq l)\sim l^{-\alpha}$ are frequently cited as evidence for complexity and serve as a starting point for linking theoretical models and mechanisms with observed…

Physics and Society · Physics 2009-11-11 M. Manning , J. M. Carlson , J. Doyle

Monthly rainfall data from June to October for 39 years was used to generate Standardized Precipitation Index (SPI) values based on Gamma distribution for a low rainfall and a high rainfall district of Andhra Pradesh state, India.…

Atmospheric and Oceanic Physics · Physics 2015-09-17 M. Naresh Kumar , C. S. Murthy , M. V. R. Sesha Sai , P. S. Roy

We propose a physics-constrained machine learning method-based on reservoir computing- to time-accurately predict extreme events and long-term velocity statistics in a model of turbulent shear flow. The method leverages the strengths of two…

Fluid Dynamics · Physics 2021-04-14 Nguyen Anh Khoa Doan , Wolfgang Polifke , Luca Magri

We investigate the long-range statistical correlations, whereby discuss the nature of the undermining interacting/ noninteracting domains and associated phase transitions under variations of the quark mass and the mass scale that…

High Energy Physics - Lattice · Physics 2019-08-19 Bhupendra Nath Tiwari

Anthropogenic warming impacts ecological communities and disturbs species interactions, particularly in temperature sensitive plant pollinator networks. While previous assessments indicate that rising mean temperatures and shifting temporal…

Populations and Evolution · Quantitative Biology 2025-04-29 Adrija Datta , Sarth Dubey , Tarik C. Gouhier , Auroop R. Ganguly , Udit Bhatia

The Gravity Recovery and Climate Experiment (GRACE) provides quantitative measures of terrestrial water storage (TWS) change. GRACE data show a significant decrease in TWS in the lower (southern) La Plata river basin of South America over…

Geophysics · Physics 2010-11-22 J. L. Chen , C. R. Wilson , B. D. Tapley , L. Longuevergne , Z. L. Yang , B. R. Scanlon

Analysis of daily streamflow variability in space and time is important for water resources planning, development, and management. The natural variability of streamflow is being complicated by anthropogenic influences and climate change,…

Water temperature and dissolved oxygen are essential indicators of water quality and ecosystem sustainability. Lately, heavy rainfalls are happening frequently and forcefully affecting the thermal structure and mixing layers in depth by…

General Economics · Economics 2024-03-20 Shabnam Salehi , Mojtaba Ardestani

Condition-Based Maintenance is pivotal in enabling the early detection of potential failures in engineering systems, where precise prediction of the Remaining Useful Life is essential for effective maintenance and operation. However, a…

Machine Learning · Computer Science 2024-06-21 Miguel Fernandes , Catarina Silva , Alberto Cardoso , Bernardete Ribeiro

Wildfires pose a significant global threat to ecosystems worldwide, with California experiencing recurring fires due to various factors, including climate, topographical features, vegetation patterns, and human activities. This study aims…

A reliable forecast of inflows to the reservoir is a key factor in the optimal operation of reservoirs. Real-time operation of the reservoir based on forecasts of inflows can lead to substantial economic gains. However, the forecast of…

Machine Learning · Computer Science 2021-09-10 Asha Devi Singh , Anurag Singh

Uncertainty in return level estimates for rare events, like the intensity of large rainfall events, makes it difficult to develop strategies to mitigate related hazards, like flooding. Latent spatial extremes models reduce uncertainty by…

Applications · Statistics 2018-12-27 Joshua Hewitt , Miranda J. Fix , Jennifer A. Hoeting , Daniel S. Cooley

The evaluation of possible climate change consequence on extreme rainfall has significant implications for the design of engineering structure and socioeconomic resources development. While many studies have assessed the impact of climate…

Applications · Statistics 2017-06-02 Poulomi Ganguli , Paulin Coulibaly

There has been active investigation into deep learning approaches for time series analysis, including foundation models. However, most studies do not address significant scientific applications. This paper aims to identify key features in…

Machine Learning · Computer Science 2025-09-22 Junyang He , Ying-Jung Chen , Alireza Jafari , Anushka Idamekorala , Geoffrey Fox

In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models…

Atmospheric and Oceanic Physics · Physics 2016-03-23 Salvatore Pascale , Valerio Lucarini , Xue Feng , Amilcare Porporato , Shabeh ul Hasson

Climate change increases the frequency of extreme rainfall, placing a significant strain on urban infrastructures, especially Combined Sewer Systems (CSS). Overflows from overburdened CSS release untreated wastewater into surface waters,…

Machine Learning · Computer Science 2025-08-13 Vipin Singh , Tianheng Ling , Teodor Chiaburu , Felix Biessmann

Spiking reservoir computing provides an energy-efficient approach to temporal processing, but reliably tuning reservoirs to operate at the edge-of-chaos is challenging due to experimental uncertainty. This work bridges abstract notions of…

Machine Learning · Computer Science 2026-04-09 Ruggero Freddi , Nicolas Seseri , Diana Nigrisoli , Alessio Basti

This paper presents a novel probabilistic approach for assessing the risk of West Nile Disease (WND) spillover to the human population. The assessment has been conducted under two different scenarios: (1) assessment of the onset of…

Applications · Statistics 2025-03-25 Saman Hosseini , Lee W. Cohnstaedt , Matin Marjani , Caterina Scoglio