5 citations · 7 across the 4 of their papers we have counts for
8 papers
BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design
Yannick Vogt, Mehdi Naouar, Maria Kalweit +4
Antibodies offer great potential for the treatment of various diseases. However, the discovery of therapeutic antibodies through traditional wet lab methods is expensive and time-c…
Advances in Land Surface Model-based Forecasting: A comparative study of LSTM, Gradient Boosting, and Feedforward Neural Network Models as prognostic state emulators
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington +7
Most useful weather prediction for the public is near the surface. The processes that are most relevant for near-surface weather prediction are also those that are most interactive…
Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design
Yannick Vogt, Mehdi Naouar, Maria Kalweit +5
The field of antibody-based therapeutics has grown significantly in recent years, with targeted antibodies emerging as a potentially effective approach to personalized therapies. S…
Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning
Lukas AW Gemein, Robin T Schirrmeister, Joschka Boedecker +1
The brain's biological age has been considered as a promising candidate for a neurologically significant biomarker. However, recent results based on longitudinal magnetic resonance…
On the Calibration of Uncertainty Estimation in LiDAR-based Semantic Segmentation
Mariella Dreissig, Florian Piewak, Joschka Boedecker
The confidence calibration of deep learning-based perception models plays a crucial role in their reliability. Especially in the context of autonomous driving, downstream tasks lik…
Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation
Andrea Ghezzi, Jasper Hoffman, Jonathan Frey +2
This work presents a novel loss function for learning nonlinear Model Predictive Control policies via Imitation Learning. Standard approaches to Imitation Learning neglect informat…