Tübingen Machine Learning
This is the youtube channel of the machine learning groups at the University of Tübingen
Probabilistic ML - 25 - Revision
Probabilistic ML - 24 - Attention
Probabilistic ML - 23 - Variational Inference
Probabilistic ML - 22 - Factorization, EM, and Responsibility
Probabilistic ML - 21 - Diffusion Models
Probabilistic ML - 20 - Markov Chain Monte Carlo
Probabilistic ML - 19 - Sampling
Probabilistic ML - 18 - Probabilistic Deep Learning
Probabilistic ML - 17 - Deep Learning
Probabilistic ML - 16 - Inference in Linear Models
Probabilistic ML - 15 - Logistic Regression
Probabilistic ML - 14 - Exponential Families
Probabilistic ML - 13 - Exponential Families
Probabilistic ML - 12 - Dynamical Systems
Probabilistic ML - 11 - Kalman Filters
Probabilistic ML - 10 - Time Series and Markov Chains
Probabilistic ML - 09 - a bit of Gaussian process theory
Probabilistic ML - 08 - Gaussian Processes by Example
Probabilistic ML - 07 - Kernels
Probabilistic ML - 06 - Gaussian Processes
Probabilistic ML - 05 - Regression
Probabilistic ML - 04 - Probabilistic Linear Algebra
Probabilistic ML - 03 - Gaussian Inference
Probabilistic ML - 02 - Densities
Probabilistic ML - 01 - Probabilities
TMLR: Connecting Parameter Magnitudes and Hessian Eigenspaces at Scale using Sketched Methods
ICLR 2025: Accelerating Neural Network Training (AlgoPerf)
Trustworthy ML - WS24/25 - Lecture 12
Trustworthy ML - WS24/25 - Lecture 11
Trustworthy ML - WS24/25 - Lecture 10