Continuum Limit
The continuum limit explores the behavior of systems as their discrete components become infinitely small, effectively transitioning from a discrete to a continuous representation. Current research focuses on understanding and quantifying the limitations of this transition in various domains, including neural networks, agent-based models, and dynamical systems, often employing techniques like metric entropy analysis and novel algorithms for improved approximation and efficiency. These investigations are crucial for advancing our understanding of complex systems and improving the performance of machine learning models and other computational methods in scenarios with limited resources or inherent constraints.
Papers
Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models
Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro
Indy Autonomous Challenge -- Autonomous Race Cars at the Handling Limits
Alexander Wischnewski, Maximilian Geisslinger, Johannes Betz, Tobias Betz, Felix Fent, Alexander Heilmeier, Leonhard Hermansdorfer, Thomas Herrmann, Sebastian Huch, Phillip Karle, Felix Nobis, Levent Ögretmen, Matthias Rowold, Florian Sauerbeck, Tim Stahl, Rainer Trauth, Markus Lienkamp, Boris Lohmann