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Artwork for Learning Bayesian Statistics

Learning Bayesian Statistics

Alexandre Andorra
Bayesian Statistics
Bayesian Inference
Machine Learning
Gaussian Processes
Causal Inference
Statistical Modeling
Pymc
Data Science
Uncertainty Quantification
Bayesian Methods
Stan
Artificial Intelligence
Sports Analytics
Variational Inference
Probabilistic Programming
Bayesian Deep Learning
Hierarchical Models
Diffusion Models
Covid-19
Generative Models

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 learnin... more

PublishesWeeklyEpisodes218Founded7 years ago
Number of ListenersCategories
TechnologyScience

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Artwork for Learning Bayesian Statistics

Latest Episodes

Today's clip is from Episode 164, featuring Andrew Gelman, Aki Vehtari & Richard McElreath. In this conversation, Andrew explains how Bayesian principal stratification can be used to reason about treatment effects when there is an intermediate treatm... more

Today's clip is from Episode 164, featuring Andrew Gelman, Aki Vehtari & Richard McElreath. In this conversation, Andrew explains why a Bayesian workflow goes far beyond simply fitting a model.

He discusses the importance of building, fitting, and ... more

Support & Resources

→ Support the show on Patreon

→ Bayesian Modeling Course (first 2 lessons free)

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

Takeaways:

Q: What is the "Bayesian W... more

Today's clip is from Episode 154, featuring Thomas Pinder. In this conversation, Thomas shares what he sees as the next steps for GPJax and how the project could become easier to use beyond its original research-focused audience.

He discusses creati... more

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Recent Guests

Dorota Vojcik
Grand prize contest winner presenting her bat mortality problem
Poland / Forest Research Institute context
Episode: #164 Bayesian Workflow, with Andrew Gelman, Aki Vehtari & Richard McElreath
Adrian Seyboldt
Researcher focused on preconditioning and Nutpie development
Flatiron Institute / PyMC Labs (via Bob Carpenter)
Episode: #163 How to make your models sample faster, with Adrian Seyboldt & Eliot Carlson
Eliot Carlson
Research analyst in Bob Carpenter's group at the Flatiron Institute, co-author on the preconditioning work
Flatiron Institute
Episode: #163 How to make your models sample faster, with Adrian Seyboldt & Eliot Carlson
Christopher Krapu
Scientist at Nvidia focusing on retrieval and agentic AI tools; long-time PyMC contributor with a background in hydrology and environmental science
Nvidia
Episode: #162 Bayesian Hydrology & GPU AI, with Christopher Krapu
Luigi Acerbi
Associate Professor of Artificial Human Intelligence at University of Helsinki; researcher in Bayesian inference and neural processes
University of Helsinki
Episode: #161 Amortized Inference & Neural Processes, with Luigi Acerbi
Vaden Masrani
Machine learning researcher turned consultant
Sophia AI Consulting
Episode: Bayesian Statistics vs Epistemology, with Vaden Masrani
Matthijs Hollanders
Postdoc focusing on wildlife data analysis and Bayesian models; creator of the Ocaroo package
University of Newcastle, Australia
Episode: #159 Bayesian Occupancy Models, with Matthijs Hollanders
Stefan Radev
Researcher/engineer focused on Amortized Bayesian Inference and SBI; involved with Baseflow/BASOL
Baseflow / BASOL
Episode: #158 Bayesian Workflows & Foundation Models, with Stefan Radev
Adam Foster
Researcher at Microsoft Research AI for Science working on Bayesian experimental design and related topics
Microsoft Research
Episode: #156 Bayesian Experimental Design & Active Learning, with Adam Foster

Host

Alex Andorra
Host of Learning Bayesian Statistics

Reviews

4.7 out of 5 stars from 252 ratings
  • Great resource

    Amazing podcast, there is hardly an episode that doesn’t send me down a new Bayesian rabbit hole!

    Apple Podcasts
    5
    Hessam Mehr
    United Kingdom3 months ago
  • Insightful podcast

    I am a newbie and I was introduced to this podcast recently. Highly recommend if you want to learn techniques and future trends (and 1001 stories around Bayesian stats) from practitioners and professionals!

    Apple Podcasts
    5
    Chi_Tuan
    Italy3 months ago
  • Best way to learn about cutting edge Bayesian statistics!

    A fantastic podcast for anyone interested in Bayesian statistics. When I hear the fun theme song I know I am about to learn something new from Alex and his heavy hitter guests! I first learned about things like amortized Bayesian inference and Nutpie from this podcast, and several episodes have given me ideas that were immediately applicable to my own work.

    Highly recommended for anyone who wants to keep up with modern applied Bayesian methods.

    Apple Podcasts
    5
    DrAleator
    United States4 months ago
  • Awesome show

    Diverse guests from many aspects of the bayesian ecosystem and intelligent interviews. Recommended!

    Apple Podcasts
    5
    Dr OfirGeva
    Israel4 months ago
  • Great show for Bayesian intuition

    The Frank Harrell episode is what gave me the epiphany and intuition about what makes Bayesian thinking so superior. Highly recommended.

    Apple Podcasts
    5
    zajichekstats
    United States4 months ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Some listeners note the host's energy and the show's ability to connect theory to practice.
Guests are consistently described as heavy-hitting and knowledgeable.
Listeners appreciate the practical focus on Bayesian workflows and real-world applications.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#147
Germany/Technology
Apple Podcasts
#77
Austria/Technology
Apple Podcasts
#89
South Korea/Technology
Apple Podcasts
#98
New Zealand/Technology
Apple Podcasts
#125
Saudi Arabia/Technology
Apple Podcasts
#228
Sweden/Technology

Talking Points

Recent interactions between the hosts and their guests.

#164 Bayesian Workflow, with Andrew Gelman, Aki Vehtari & Richard McElreath
Q: What is a key new insight added to teaching Bayesian workflow?
The most important addition is making the structure of the workflow explicit, with diagrams and narratives that distinguish workflow from a simple pipeline and highlight why and how inputs are combined at each decision point.
#164 Bayesian Workflow, with Andrew Gelman, Aki Vehtari & Richard McElreath
Q: What is the elevator pitch of the Bayesian Workflow book and its intended audience?
The book aims to codify a practical, engineering-style approach to Bayesian analysis that goes beyond teaching methods to guiding the entire decision-making workflow, using simulations, priors, diagnostics, and case studies to help practitioners handle real-world data and uncertainties.
Bayesian Epistemology Is "Bayes' Theorem Without the Data"
Q: The main thing that bothers you about Bayesian epistemology is that is in the scenarios where you don't have data to update your beliefs. Is that correct?
The host and guest discuss that the core issue is the lack of data to legitimately update beliefs, which makes Bayesian reasoning fragile or misleading when detached from empirical evidence.
#162 Bayesian Hydrology & GPU AI, with Christopher Krapu
Q: What guidance would you give to someone deciding whether to use GPU acceleration for a Bayesian model?
Prefer GPU when your likelihood evaluations or gradient computations involve large matrices or large arrays; if the model heavily uses recurrency or Python-level loops, a GPU may be less helpful. The key is to map the computation to large, parallelizable operations and leverage gradient-based samplers like HMC/VI.
#162 Bayesian Hydrology & GPU AI, with Christopher Krapu
Q: From a long-time PyMC contributor perspective, what is the current state of Bayesian tooling at scale and what bottlenecks remain?
GPU-backed backends (e.g., PyMC with JAX, Pyro, NumPyro) have made big Bayesian models practical, but scaling bureaucracy and benchmarking across languages and platforms remains a bottleneck; ongoing work should focus on cross-framework interoperability, broader sharing of benchmarks, and easier adoption for practitioners outside academia.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

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Frequently Asked Questions About Learning Bayesian Statistics

What is Learning Bayesian Statistics about and what kind of topics does it cover?

A technically rich program focused on Bayesian methods across science and industry, with guests ranging from ecological modeling to AI systems and probabilistic programming. Listeners are treated to practical workflows, tooling tips, and discussions about how Bayesian thinking informs model design, uncertainty quantification, and decision making in real-world settings. The show frequently features deep dives into computational strategies, prior elicitation, and scalable inference, often balancing rigorous theory with actionable guidance. A notable strength is the willingness to critique methods and share failures alongside successes, making it useful for practitioners who want to apply Bayesian statistics and stay current with the ecosystem... more

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1. Machine Learning Street Talk (MLST)
2. Super Data Science: ML & AI Podcast with Jon Krohn
3. Python Bytes
4. Google DeepMind: The Podcast
5. Talk Python To Me

How many episodes of Learning Bayesian Statistics are there?

Learning Bayesian Statistics launched 7 years ago and published 218 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Learning Bayesian Statistics?

Recent guests on Learning Bayesian Statistics include:

1. Dorota Vojcik
2. Adrian Seyboldt
3. Eliot Carlson
4. Christopher Krapu
5. Luigi Acerbi
6. Vaden Masrani
7. Matthijs Hollanders
8. Stefan Radev

To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.

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