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We describe a short, reproducible workflow for applying finite differences on nonuniform grids determined by a positive weight function g. The grid is obtained by equidistribution, mapping uniform computational coordinates $\xi\in[0,1]$ to…
Heterogeneous federated learning (HFL) aims to ensure effective and privacy-preserving collaboration among different entities. As newly joined clients require significant adjustments and additional training to align with the existing…
Implicit generative models, which do not return likelihood values, such as generative adversarial networks and diffusion models, have become prevalent in recent years. While it is true that these models have shown remarkable results,…
Energy systems modellers often resort to simplified system representations and deterministic model formulations (i.e., not considering uncertainty) to preserve computational tractability. However, reduced levels of detail and neglected…
Due to limited metering infrastructure, distribution grids are currently challenged by observability issues. On the other hand, smart meter data, including local voltage magnitudes and power injections, are communicated to the utility…
These notes describe CO2eq a tool that estimates $CO_2$ equivalent emissions associated with air traffic and applies it to the Internet Engineering Task Force (IETF), an international standard developing organization that meets 3 times a…
Grid energy storage can help to balance supply and demand, but its financial viability and operational carbon emissions impact is poorly understood because of the complexity of grid constraints and market outcomes. We analyse the impact of…
Consider one realization of a continuous-time Gaussian process $Z$ which belongs to the Mat\' ern family with known ``regularity'' index $\nu >0$. For estimating the autocorrelation-range and the variance of $Z$ from $n$ observations on a…
Climate change is profoundly affecting nearly all aspects of life on earth, including human societies, economies and health. Various human activities are responsible for significant greenhouse gas emissions, including data centres and other…
Graph edit distance (GED) is a powerful and flexible graph matching paradigm that can be used to address different tasks in structural pattern recognition, machine learning, and data mining. In this paper, some new binary linear programming…
In order to achieve greenhouse gas neutrality by 2045, the Climate Protection Act sets emission reduction targets for the years 2030 and 2040, as well as decreasing annual emission volumes for some sectors, including the building sector.…
Climate change and global warming have been trending topics worldwide since the Eco-92 conference. However, little progress has been made in reducing greenhouse gases (GHGs). The problems and challenges related to emissions are complex and…
Currently, the world experiences an unprecedentedly increasing generation of application data, from sensor measurements to video streams, thanks to the extreme connectivity capability provided by 5G networks. Going beyond 5G technology,…
This paper examines how firm-level determinants of industrial emissions evolve over time as firms adapt to environmental regulation, economic conditions, and organisational constraints. Using a panel of 204 U.S. industrial facilities…
The past 20 years have brought fundamental advances in modeling unobserved heterogeneity in panel data. Interactive Fixed Effects (IFE) proved to be a foundational framework, generalizing the standard one-way and two-way fixed effects…
Modern grid monitoring equipment enables utilities to collect detailed records of power interruptions. These data are aggregated to compute publicly reported metrics describing high-level characteristics of grid performance. The current…
Environmental, Social, and Governance (ESG) data provides non-financial insights into corporations. In this study, we aim to identify relevant ESG raw variables to assess financial risk, measured by logarithmic volatility of return. We…
Many organizations, including governments, utilities, and businesses, have set ambitious targets to reduce carbon emissions for their Environmental, Social, and Governance (ESG) goals. To achieve these targets, these organizations…
We consider linear structural equation models that are associated with mixed graphs. The structural equations in these models only involve observed variables, but their idiosyncratic error terms are allowed to be correlated and…
Ecodriving guidance includes courses or suggestions for human drivers to improve driving behaviour, reducing energy use and emissions. This paper presents a systematic review of existing eco-driving guidance studies and identifies…