AI Summer School 2023 Posters
The book of poster abstracts is available online.
The followings are the PDF files of presented posters, arranged alphabetically by title:
- Alphafold - Colin Zach - PDF
- Automatic Symbolic Differentiation for Tensor Expressions - Farin Lippmann - PDF
- Exploring Optical Artificial Neural Inference - Matin Dehghani - PDF
- MSNovelist: de novo structure generation from mass spectra - Jonas Emmert - PDF
- Self Supervised Learning for Robustness and OOD Detection - Nick Würflein - PDF
- StyleGAN-Structure and Applications - Lucas Fabian Naumann - PDF
- Summarizing: A Machine Learning Approach for Classifying Ischemic Stroke Onset Time from Imaging - Daria Glaser - PDF (Best Poster Award 🏆)
- The Long Road to Artificial General Intelligence - Daniel Motz - PDF (Best Poster Award 🏆)
- Using Tensor Processing Units for Neural Networks - Jonas Engicht - PDF
- Wie lernen Künstliche Intelligenzen? - Paula Kecke - PDF
- AI in Cancer Research - Rayk Kretzschmar - PDF
- AI-based High-Level Decision Making in Highway Autonomous Driving - Jiachen Gong - PDF
- Artificial Intelligence in Laser Beam Machining - Anukul Jovial Augustine - PDF
- Backpropagation-based visualization methods for explaining CNNs - Christian Ickler - PDF
- Causes for the Failure of Machine Learning Projects in Productive Use - Mia Ohlrogge - PDF
- Chip Design with Deep Reinforcement Learning - Bohdan Babii - PDF
- Computing einsum expressions using LIBXSMM - Max Koch - PDF (Best Poster Award 🏆)
- DB Systems optimised for ML - Tamino Steinert - PDF (Best Poster Award 🏆)
- Forward Looking Active Retrieval Augmented Generation - Lukas Zeit-Altpeter - PDF