Learning Bayesian Statistics

#71 Artificial Intelligence, Deepmind & Social Change, with Julien Cornebise

Nov 14, 2022
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1
Introduction
00:00 • 4min
2
How Did You Come to the Math in Stats Worlds?
03:38 • 2min
3
How Did You Get Into Bayesian Analysis?
05:15 • 3min
4
DeepMind - How Did Bayesian Deep Learning Help You?
07:53 • 3min
5
Is There a Difference Between Bayesian and Frequency?
11:19 • 2min
6
The Probabilistic View or the Bayesian View or Machine Learning?
12:56 • 2min
7
Optical Program Tomography - What Did You Learn?
15:05 • 3min
8
AI for Good
18:19 • 3min
9
The Quantitative Approach to Crowdsourcing on Twitter
21:39 • 3min
10
Is Stable Diffusion Really a New Model?
24:55 • 2min
11
Using Stable Diffusion to Generate Full Resolution Images
26:58 • 3min
12
Deep Learning
29:56 • 5min
13
GPs and Deep Neural Networks Are Related
34:32 • 2min
14
Do You Think Deep Learning Will Work?
36:24 • 4min
15
Stable Diffusion
40:38 • 2min
16
Automated Priori Sensitivity Analysis
42:24 • 2min
17
What Are the Most Important Skills That You're Trying to Instill in Your Students?
44:53 • 4min
18
Is There Serendipity in Machine Learning?
48:38 • 3min
19
What Are the Best Ways to Communicate About Science?
51:52 • 2min
20
Don't Dumb It Down
53:48 • 2min
21
The Biggest Problems in Bayesian Deep Learning
55:56 • 4min
22
The Show You, You've Been Really Generous With Your Term, Junior
59:48 • 1min
23
What Are You the Good to Guide For?
01:01:17 • 2min
24
A Stable Diffusion With the Prom
01:02:50 • 2min