Charts
Learning Bayesian StatisticsEpisode from the podcastLearning Bayesian Statistics
BITESIZE | What's Missing in Bayesian Deep Learning?

BITESIZE | What's Missing in Bayesian Deep Learning?

BonusReleased Wednesday, 13th August 2025
Good episode? Give it some love!
BITESIZE | What's Missing in Bayesian Deep Learning?

BITESIZE | What's Missing in Bayesian Deep Learning?

BITESIZE | What's Missing in Bayesian Deep Learning?

BITESIZE | What's Missing in Bayesian Deep Learning?

BonusWednesday, 13th August 2025
Good episode? Give it some love!
Rate Episode
List
About
InsightsPodchaser Pro
Reviews
Credits
1
Lists
Transcript

Today’s clip is from episode 138 of the podcast, with Mélodie Monod, François-Xavier Briol and Yingzhen Li.

During this live show at Imperial College London, Alex and his guests delve into the complexities and advancements in Bayesian deep learning, focusing on uncertainty quantification, the integration of machine learning tools, and the challenges faced in simulation-based inference.

The speakers discuss their current projects, the evolution of Bayesian models, and the need for better computational tools in the field.

Get the full discussion here.

Attend Alex's tutorial at PyData Berlin: A Beginner's Guide to State Space Modeling 


Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!

Visit our Patreon page to unlock exclusive Bayesian swag ;)

Transcript

This is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.

Show More
Rate
List
Get this podcast via API

From The Podcast

712
Are you a researcher or data scientist / analyst / ninja? Do you want to learn Bayesian inference, stay up to date or simply want to understand what Bayesian inference is?Then this podcast is for you! You'll hear from researchers and practitioners of all fields about how they use Bayesian statistics, and how in turn YOU can apply these methods in your modeling workflow.When I started learning Bayesian methods, I really wished there were a podcast out there that could introduce me to the methods, the projects and the people who make all that possible. So I created "Learning Bayesian Statistics", where you'll get to hear how Bayesian statistics are used to detect black matter in outer space, forecast elections or understand how diseases spread and can ultimately be stopped.But this show is not only about successes -- it's also about failures, because that's how we learn best. So you'll often hear the guests talking about what *didn't* work in their projects, why, and how they overcame these challenges. Because, in the end, we're all lifelong learners!My name is Alex Andorra by the way, and I live in Estonia. By day, I'm a data scientist and modeler at the PyMC Labs consultancy. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the python packages PyMC and ArviZ. I also love election forecasting and, most importantly, Nutella. But I don't like talking about it – I prefer eating it.So, whether you want to learn Bayesian statistics or hear about the latest libraries, books and applications, this podcast is for you -- just subscribe! You can also support the show and unlock exclusive Bayesian swag on Patreon!

Join Podchaser to...

  • Rate podcasts and episodes
  • Follow podcasts and creators
  • Create podcast and episode lists
  • & much more
Do you host or manage this podcast?
Claim and edit this page to your liking.
,
Podchaser Logo

Podchaser is the ultimate destination for podcast data, search, and discovery. Learn More