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65. Designing Generative Models (with Pierre Glaser)

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Content provided by Neuroverse. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Neuroverse or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In today's episode we are joined by Pierre Glaser to discuss designing generative models. Pierre Glaser is a PhD student in Machine Learning at the Gatsby Computational Neuroscience Unit in UCL. He is working with Professor Arthur Gretton on advancing the methodology of flexible generative modelling. We discuss what generative models are (such as ChatGPT, Dall-E), what fitting a probabilistic model to a dataset entails, how physics and neuroscience are used in these models, and many more captivating topics! Today’s episode was made possible thanks to the support of the Sainsbury Wellcome Public Engagement fund. We would like to thank Sainsbury Welcome Centre (SWC) for the generous grant supporting Science Communication initiatives like these. ⁠https://www.sainsburywellcome.org/web/⁠

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We hope you enjoy the episode! Please feel free to share with your friends and family, it means a lot to us🤍

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82 episodes

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Manage episode 389300235 series 3412534
Content provided by Neuroverse. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Neuroverse or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In today's episode we are joined by Pierre Glaser to discuss designing generative models. Pierre Glaser is a PhD student in Machine Learning at the Gatsby Computational Neuroscience Unit in UCL. He is working with Professor Arthur Gretton on advancing the methodology of flexible generative modelling. We discuss what generative models are (such as ChatGPT, Dall-E), what fitting a probabilistic model to a dataset entails, how physics and neuroscience are used in these models, and many more captivating topics! Today’s episode was made possible thanks to the support of the Sainsbury Wellcome Public Engagement fund. We would like to thank Sainsbury Welcome Centre (SWC) for the generous grant supporting Science Communication initiatives like these. ⁠https://www.sainsburywellcome.org/web/⁠

---

We hope you enjoy the episode! Please feel free to share with your friends and family, it means a lot to us🤍

Neuroverse Website

⁠⁠⁠⁠⁠⁠https://neuroversepod.com⁠⁠⁠⁠⁠⁠

Podcast directory

⁠⁠⁠⁠⁠⁠⁠https://anchor.fm/neuroverse9⁠⁠⁠⁠⁠⁠⁠

Support us!

⁠⁠⁠⁠⁠⁠⁠https://ko-fi.com/neuroverse⁠⁠⁠⁠⁠⁠⁠

Twitter: @neuroverse_pod

⁠⁠⁠⁠⁠⁠https://twitter.com/neuroverse_pod?s=21&t=KvAEuwGNKFQ9IPKlL7NTEg⁠⁠⁠⁠⁠⁠

Instagram: @Neuroverse_pod

⁠⁠⁠⁠⁠⁠https://instagram.com/neuroverse_pod?igshid=YmMyMTA2M2Y=⁠⁠⁠⁠⁠⁠

Help us improve our podcast by giving us some feedback!

⁠⁠⁠⁠⁠⁠https://forms.gle/PuEMC1BCWXdAqCRQA⁠

  continue reading

82 episodes

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