diff --git a/_teaching/2024-SS-Machine-Perception.html b/_teaching/2024-SS-Machine-Perception.html index 4ecf3c7..a5b9e78 100644 --- a/_teaching/2024-SS-Machine-Perception.html +++ b/_teaching/2024-SS-Machine-Perception.html @@ -1,6 +1,6 @@ --- title: Machine Perception -ref: mp2023 +ref: mp2024 description: semester: Spring 2023 number: 263-3710-00L @@ -62,384 +62,7 @@

Schedule

Wk.Date ContentMaterial Exercise Session - -
- slides pt. II
- - - Perceptron Visualization Notebook
- - - -

Tutorial Implement your own MLP

- slides
- XOR Notebook
- XOR Solutions
- Eye-Gaze Notebook
- Eye-Gaze Solutions
-

Tutorial Linear Regr.

- slides
- Linear Regression Notebook
- -

Pen & Paper Backprop.

- exercise
- exercise solution
- - - - - 3 - 09.03.
10.03. - -
Convolutional Neural Networks
- - -

- slides pt. I
- - slides pt. II
- -

-

Additional material: -
- RSVP -
- Cortical Neuron --> -

- - - -

Tutorial CNNs in Pytorch

- slides
- CNN Notebook

- -

Pen & Paper CNN

- exercise
- exercise solution
- - - - - - 4 - 15.03. - -
Fully Convolutional Neural Networks
- - - slides - - - - - - - 4 - 16.03. - -
Recurrent Neural Networks

LSTM, GRU, Backpropagation through time

- - - slides
- - - -

Tutorial RNNs in Pytorch

- slides
- RNN Notebook
-
-

Pen & Paper RNN

- exercise
- exercise solution
- - - - - - 5 - 23.03.
24.03 - -
Generative Models Pt. I: Latent Variable Models

Variational Autoencoders, etc.

- - -

- slides pt. I
- slides pt. II -

- - - - -

Class Tips for Training I

- slides
-
-

Pen & Paper VAE

- exercise
- exercise solution
- - - - - - - 6 - 30.03.
31.03. - -
Generative Models Pt. II: Autoregressive Models

PixelCNN, PixelRNN, WaveNet, Stochastic RNNs

- - - slides pt. I
- slides pt. II -
- - -

Class Tips for Training II

- slides
-

Pen & Paper AR

- exercise
- exercise solution
- - - - - - - 7 - 05.04.
06.04. - -
Generative Models Pt. III: Normalizing Flows and Invertible Neural Networks

- - -

- slides NF Pt. I -
- slides NF Pt. II -
-

- - - -

Pen & Paper NF

- exercise
- exercise solution
- - - - - 8 - 12.04.
23.04. - -
-- No Class (Easter) --
- - - - - - - 9 - 19.04.
20.04. - -
Generative Models Pt. IV: Implicit Models

Generative Adversarial Networks & Co

- - - slides GAN Pt. I -
- slides GAN Pt. II -
- - -

Tutorial Exercise Discussion and Euler

- slides PP Backprop&CNN
- slides Euler
-

Pen & Paper GAN

- exercise -
- exercise solution -
- - - - 10 - 26.04
27.04 - -
Generative Models Pt. V: GAN Applications and Diffusion Models
- - - slides GAN Pt. III -
- slides Diffusion Models -
- - -

Pen & Paper class Diffusion Models

- exercise -
- exercise solution -
- - - - 11 - 03.05
04.05 - -
Implicit Surfaces and Neural Radiance Fields
- - - slides NIR Pt. I -
- slides NIR Pt. II -
- - -

Tutorial Exercise Discussion AR

- slides
-

Pen & Paper class Implicit Surfaces

- exercise -
- exercise solution -
- - - - - - 12 - 10.05.
11.05. - -
Parametric Human Body Models and Applications

- - - slides PBM -
- - -

Tutorial Exercise Discussion GAN & NF

- slides
-

Pen & Paper PBM

- exercise -
- exercise solutions -
- - - - - 13 - 17.05.
18.05. - -
-- No classes or exercise sessions --
- - - - - - - - - 13 - 24.05.
25.05. - -
Reinforcement Learning
- - - slides RL pt. I
- slides RL pt. II
- - -

Pen & Paper RL

- exercise
- exercise solutions
- - - - - 14 - 01.06 - -
AIT Open House
- - - - - - - - 07.06 - -
Exam (13:30 - 16:30; HIL E 3, HIL E 4)
- - - - - - - - 27.07 / 28.07 - -
Exam Review (14:00 - 15:00; Location ML F 39)
- - - - ---> - +