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65. Designing Generative Models (with Pierre Glaser)

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Contenuto fornito da Neuroverse. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Neuroverse o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.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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81 episodi

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iconCondividi
 
Manage episode 389300235 series 3412534
Contenuto fornito da Neuroverse. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Neuroverse o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.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

--- Send in a voice message: https://podcasters.spotify.com/pod/show/neuroverse9/message
  continue reading

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