55:37

Trustworthy ML - WS24/25 - Lecture 12

01:34:17

Trustworthy ML - WS24/25 - Lecture 11

01:30:49

Trustworthy ML - WS24/25 - Lecture 10

01:34:07

Trustworthy ML - WS24/25 - Lecture 9

01:44:53

Trustworthy ML - WS24/25 - Lecture 6 (revised)

01:32:11

Trustworthy ML - WS24/25 - Lecture 8

01:32:01

Trustworthy ML - WS24/25 - Lecture 7

01:23:23

Trustworthy ML - WS24/25 - Lecture 6

01:29:14

Trustworthy ML - WS24/25 - Lecture 5

01:27:01

Trustworthy ML - WS24/25 - Lecture 4

01:25:00

Trustworthy ML - WS24/25 - Lecture 3

01:29:36

Trustworthy ML - WS24/25 - Lecture 2

01:33:12

Trustworthy ML - WS24/25 - Lecture 1

01:44:51

Aggregation

01:39:13

The Categorical Imperative

01:42:35

Ethics as a Technological Problem

01:23:42

What is to be done? (context)

01:44:54

Data

01:48:25

How to think about Technologies

01:24:09

The Construction of Data and Distributions

01:28:17

What is to be done? (rhetoric)

01:39:06

Individual Fairness, Privacy and other Information-based Harms

01:37:18

Challenges of Choice of Fairness Measure

01:31:04

Aggregation Functionals

01:42:00

Introduction, Standard Approaches, and the Cost of Fairness

01:24:26

Theorie II - 26 - Zusammenfassung & Abschluss

01:29:35

Theorie II - 25 - Information & Zufall

01:31:10

Theorie II - 24 - In NP, um NP, und um NP herum

05:03

ICML 2024: Differentiable Annealed Importance Sampling Minimizes The JS-Divergence (Zenn, Bamler)

01:19:41

Theorie II - 22 - Satz von Cook & Levin

01:13:18

Theorie II - 21 - NP-Vollständigkeit

01:25:36

Theorie II - 20 - P != NP?

01:17:55

Theorie II - 18 - Komplexität

01:27:44

Theorie II - 19 - P und NP

01:30:10

Theorie II - 17 - Rekursive Funktionen

01:23:55

Theorie II - 16 - Turing-Vollständigkeit und - Äquivalenz

01:24:55

Theorie II - 12 - Nicht Erkennbar / Nicht Entscheidbar

01:21:17

Theorie II - 15 - Das Post'sche Korrespondenzproblem

01:23:52

Theorie II - 14 - Satz von Rice

01:26:38

Theorie II - 13 - Reduktionen

01:28:14

Theorie II - 11 - Abzählbarkeit

01:23:26

Theorie II - 09 - Turingmaschinen

01:26:36

Theorie II - 08 - Deterministische Kontextfreie Grammatiken

01:28:47

Theorie II - 07 - Kellerautomaten

01:25:49

Theorie II - 06 - Kontextfreie Grammatiken

01:23:40

Theorie II - 05 - Das Pumping-Lemma

01:28:58

Theorie II - 04 - Reguläre Ausdrücke

01:20:47

Theorie II - 03 - Nichtdeterministische Endliche Automaten

01:25:45

Theorie II - 02 - Deterministische Endliche Automaten

01:15:39

Theorie II - 01 - Formale Sprachen

01:26:39

Trustworthy ML - Lecture 12 - Conclusion (Exam, Final topics, Research at STAI)

01:29:53

Trustworthy ML - Lecture 11 - Uncertainty (Aleatoric uncertainty, Factorisation)

01:19:26

Trustworthy ML - Lecture 10 - Uncertainty (Definitions & evaluation, Epistemic uncertainty)

37:59

Virtual Humans -- Lecture 07.2 Fitting SMPL to IMU Learning

32:03

Virtual Humans -- Lecture 09.1 Neural Implicits and Point Based Clothing Models PART2

32:59

Virtual Humans -- Lecture 09.1 Neural Implicits and Point Based Clothing Models PART3 and PART4

32:03

Virtual Humans -- Lecture 09.1 Neural Implicits and Point Based Clothing Models PART2

27:15

Virtual Humans -- Lecture 09.1 Neural Implicits and Point Based Clothing Models PART1

01:20:51

Trustworthy ML - Lecture 9 - Uncertainty (Definitions & evaluation)

01:30:32

Trustworthy ML - Lecture 8 - Explainability (Training data attribution)