# ML for Fast Simulation

- Institution: CERN
- Department: CERN openlab Summer Student Programme 2023
- Speaker: Zeeshan Memon
- Year: 2023
- Language: English
- Source: [CERN](https://videos.cern.ch/record/3011944)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

High-energy physics (HEP) experiments rely on Monte Carlo (MC) simulation to test hypotheses and understand data distributions. To meet the demand for fast and large-scale simulated samples, novel Fast Simulation techniques have emerged, including neural network models. This project explores the application of a large-scale transformer-based model, leveraging recent advancements in foundation models (e.g., GPT-3, Dall-E-2), for fast simulation in HEP. My contribution involves working on preprocessing and loss function design to enhance the efficiency and accuracy of the proposed transformer-based model and compare their results with other existing methodologies..

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## Lectures

1. [ML for Fast Simulation](https://invisiblenetwork.ai/learn/cern/3011944/88de20f23ab6), 8 min (CERN's player)