Custom Manufacturing Industry podcast is an entrepreneurship and motivational podcast on all platforms, hosted by Aaron Clippinger. Being CEO of multiple companies including the signage industry and the software industry, Aaron has over 20 years of consulting and business management. His software has grown internationally and with over a billion dollars annually going through the software. Using his Accounting degree, Aaron will be talking about his organizational ways to get things done. Hi ...
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Indhold leveret af The Quant / Financial Engineering Podcast and Patrick J Zoro. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Quant / Financial Engineering Podcast and Patrick J Zoro eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
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Bayesian Neural Networks
MP3•Episode hjem
Manage episode 448852041 series 2686124
Indhold leveret af The Quant / Financial Engineering Podcast and Patrick J Zoro. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Quant / Financial Engineering Podcast and Patrick J Zoro eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Edris Loftpouri MFE /24 discusses his interest on the implementation of Bayesian Neural Networks (BNNs) for macroeconomic forecasting. He also touches on Castastrophe Modeling https://www.linkedin.com/in/patrick-z-08bb5b5a/ https://www.linkedin.com/company/lehigh-master-in-financial-engineering/ This project develops a Bayesian Neural Network (BNN) for macroeconomic forecasting, using stochastic volatility and Bayesian shrinkage priors to manage complex, high-dimensional data. With layer-specific and neuron-specific activation functions, the model captures both long-term dependencies and short-term nonlinear dynamics. Offering adaptive uncertainty quantification and robust volatility handling, it’s ideal for risk analysis, economic policy, and quantitative finance applications. https://www.linkedin.com/in/edris-lotfpouri/
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58 episoder
MP3•Episode hjem
Manage episode 448852041 series 2686124
Indhold leveret af The Quant / Financial Engineering Podcast and Patrick J Zoro. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Quant / Financial Engineering Podcast and Patrick J Zoro eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Edris Loftpouri MFE /24 discusses his interest on the implementation of Bayesian Neural Networks (BNNs) for macroeconomic forecasting. He also touches on Castastrophe Modeling https://www.linkedin.com/in/patrick-z-08bb5b5a/ https://www.linkedin.com/company/lehigh-master-in-financial-engineering/ This project develops a Bayesian Neural Network (BNN) for macroeconomic forecasting, using stochastic volatility and Bayesian shrinkage priors to manage complex, high-dimensional data. With layer-specific and neuron-specific activation functions, the model captures both long-term dependencies and short-term nonlinear dynamics. Offering adaptive uncertainty quantification and robust volatility handling, it’s ideal for risk analysis, economic policy, and quantitative finance applications. https://www.linkedin.com/in/edris-lotfpouri/
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