Listen Score
LS 41
Global Rank
TOP 1.5%

ОБ ЭТОМ ПОДКАСТЕ 🔗

Ведущие:
Частота обновления:
every 6 days
Средняя продолжительность аудио:
57 minutes
Гостевые интервью
Имеет спонсоров
английский
США
222 серий
с 20 сентября 2019 г.
episodic

AUDIENCE OF THIS PODCAST 🔗

~54.82% of listeners are from United States.
🇺🇸
US
54.82%
🇬🇧
GB
15.32%
🇨🇦
CA
7.79%
🇩🇪
DE
3.17%
🇧🇷
BR
1.71%
🇷🇴
RO
1.58%
🇪🇸
ES
1.45%
🇫🇮
FI
1.32%
🇮🇳
IN
1.18%
🇫🇷
FR
1.18%
🇦🇺
AU
1.05%
🇦🇷
AR
0.92%
🇸🇪
SE
0.79%
🇮🇹
IT
0.79%
🇰🇷
KR
0.66%
🇨🇿
CZ
0.66%
🇿🇦
ZA
0.66%
🇱🇺
LU
0.66%
🇧🇬
BG
0.52%
🇳🇱
NL
0.39%
🇦🇹
AT
0.39%
🇲🇽
MX
0.26%
🇳🇿
NZ
0.26%
🇧🇪
BE
0.26%
🇽🇰
XK
0.26%
🇰🇪
KE
0.13%
🇮🇪
IE
0.13%
🇸🇩
SD
0.13%
🇹🇼
TW
0.13%
🇹🇷
TR
0.13%
🇸🇦
SA
0.13%
🇺🇦
UA
0.13%
🇪🇹
ET
0.13%
🇸🇬
SG
0.13%
🇳🇬
NG
0.13%
🇨🇱
CL
0.13%
🇮🇶
IQ
0.13%
🇵🇦
PA
0.13%
🇳🇴
NO
0.13%
Others
0.13%
* Data source: directly measured on Listen Notes. в реальном времени

ПОСЛЕДНИЙ ЭПИЗОД 🔗

Today's clip is from Episode 166, featuring Bill Engels & Jesse Grabowski. In this conversation, Bill explains what a kernel means in a Gaussian process and how it defines the idea of similarity between data points. He then breaks down the role of the length scale, showing how it controls how q…

ПОИСК ПРОШЛЫХ ЭПИЗОДОВ

Искать прошлые эпизоды Learning Bayesian Statistics.

ПРЕДЫДУЩИЕ ЭПИЗОДЫ

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 PTGP and why did Bill and Jesse build it?A: PTGP is a new Gaussi…
Today's clip is from Episode 165, featuring Alex Fengler. In this conversation, Alex introduces Bayesify , a tool that uses AI to analyze research papers and assess how well they follow a Bayesian workflow.He explains how the tool breaks an analysis down step by step, identifies strengths and weakn…
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 HSSM and how does it relate to HDDM?A: HSSM stands for hierarchi…
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 treatment or outcome that is only partially observe…
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 checking models, and why moving between simpler…
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 Workflow" book about, and who is it for? A: It cove…
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 creating a higher-level interface that could make fitting…
Today's clip is from Episode 163, featuring Eliot Carlson and Adrian Seyboldt. In this conversation, Eliot and Adrian look beyond current approaches to HMC adaptation and preconditioning and share the ideas they're most excited to explore next.Eliot discusses new ways of parallelizing MCMC by solvi…
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 mass matrix adaptation, in plain terms?A: Mass matrix adaptation i…
Отказ от ответственности: Подкаст и иллюстрации, встроенные в эту страницу, взяты из Alexandre Andorra, который является собственностью его владельца и не связан или не одобрен Listen Notes, Inc.