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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

31.08.2022

Fulbright PULSE podcast on Prof. Cremers went online on Apple Podcasts and Spotify.

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Seminar: Deep Learning for the Natural Sciences (5 ECTS)

Summer Semester 2024

Organiser: Karnik Ram

08-02-2024: Preliminary meeting slides

22-01-2024: Preliminary meeting will take place on 08.02.2024 between 14:00 - 15:00 online (zoom link). Attendance is highly encouraged, but not mandatory.

Description

Following its success in computer vision and language processing, deep learning is now being increasingly used to augment and accelerate research in the natural sciences. Examples include electro-catalyst discovery for energy storage, fast PDE solvers for weather forecasting, discovery of new anti-biotics, and many other advances that were not possible using traditional methods alone. In this seminar, we will discuss relevant papers in this new area, with an emphasis on the deep learning techniques powering these approaches such as geometric deep learning, generative models, and self-supervised learning.

Format
  • Students are expected to study one paper in depth, and present and lead a discussion on it. Apart from the presentation and report, students are also expected to periodically submit one-paragraph summaries of the papers discussed, and participate in the discussions.
  • Sessions will be held in-person (with a remote attendance option) once every two weeks, on Tueday afternoon (14:30 - 16:30). There will be two paper presentations in every session. There may also be a catch-up lecture on certain relevant topics from deep learning (eg. diffusion models, graph learning) at the start based on interest.
Prerequisites

A good understanding of machine learning techniques (esp. deep learning), linear algebra, and calculus. Undergraduate students are requested to check with the organizer before enrolling.

Tentative list of papers
Schedule

TBA

Additional Resources

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

News

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

31.08.2022

Fulbright PULSE podcast on Prof. Cremers went online on Apple Podcasts and Spotify.

More