de | en

Advanced Deep Learning for Physics (IN2298)

Course 0000003205 in SS 2018

General Data

Course Type lecture
Semester Weekly Hours 4 SWS
Organisational Unit Informatics 15 - Chair of Computer Graphics and Visualization (Prof. Westermann)
Lecturers Marie-Lena Eckert
Responsible/Coordination: Nils Thürey

Assignment to Modules

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks This course targets machine learning techniques and numerical simulation algorithms for materials such as fluids and deformable objects in the context of computer animation. The lecture and exercises will all be in English. The following topics are discussed: - Convolutional neural networks & deep learning techniques - Physically-based animation, fluid modeling - Discretizations, and partial differential equations - Exercises to gain hands-on experience with CNN training and fluid simulation algorithms More information:
Links E-Learning course (e. g. Moodle)
TUMonline entry

Equivalent Courses (e. g. in other semesters)

SS 2022 Advanced Deep Learning for Physics (IN2298) Chen, L. Holl, P. List, B. Weitz, S.
Responsible/Coordination: Thürey, N.
Tue, 16:00–18:00, MI HS2
Fri, 08:00–10:00, MI HS2
SS 2017 Deep Learning and Numerical Simulations for Visual Effects (IN2298) Eckert, M.
Responsible/Coordination: Thürey, N.
SS 2016 Simulation for Visual Effects (IN2298)
SS 2015 Simulation for Visual Effects (IN2298)
Top of page