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October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.

 

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Automation of the Approach to Replicating Data When the Control Group Is Depleted in The Difference-In-Differences Method: Application to IRB Implementation Data Samples

Procedia Computer Science. 2022. Vol. 199. P. 231–237.
Penikas H. I., Скареднова А. Э., Surkov M., Феста Ю. Ю.

Internal-Ratings Based (IRB) approach is one of the founding blocks in the modern credit risk management and regulation. Its implementations by the banks world-wide incentivizes researchers, central bankers and investors to evaluate the outcome versus the non-IRB banks, i.e., the treatment effect. However, there are obstacles in such evaluation. From one side, all the banks may transit to IRB for a relatively modest economy (like Greece). From another side, there is no single IRB transition point (like in the EU where the transition is voluntarily; a single point exists for the USA where the transition was mandatory for the largest banks). That is why we discuss the problem of the ‘control’ group depletion (attrition) in the Difference-in-Differences method. We provide two ways to replicate data using python language. The first code is based on the matrix structure (object * time), the second – panel data structure. Comparing both ways of the data replication (resampling) we choose the second algorithm due to it versality and faster computing results, than the first one.

Language: English
DOI
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Keywords: pythondifference-in-differencereplicationIRBresampling
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