2 citations · 3 across the 8 of their papers we have counts for
15 papers
Multi-modal transformer for signal classification in nanopore blockade experiments
Sandro Kuppel, Julian Hoßbach, Samuel Tovey +1
Nanopore devices have emerged as powerful tools for single-molecule sensing, with potential for rapid, portable diagnostics. They detect changes in ionic current as analytes enter…
Reinforcement Learning Enables Autonomous Microrobot Navigation and Intervention in Simulated Blood Capillaries
Jannik Drotleff, Samuel Tovey, Paul Hohenberger +4
Autonomous microrobots navigating biological vasculature could enable targeted drug delivery and thrombolysis, yet training control policies for realistic environments remains an o…
Spectral Reach: Understanding Neural Scaling as Progress into the Spectral Tail
Konstantin Nikolaou, Jonas Scheunemann, Sven Krippendorf +2
Neural scaling laws describe predictable power-law relationships between model size, dataset size, compute, and performance. While these laws guide the development of modern founda…
Deep Learning-Driven Peptide Classification in Biological Nanopores
Julian Hoßbach, Samuel Tovey, Sandro Kuppel +3
Nanopore-based single-molecule sensing is a promising route to fast, low-cost disease diagnosis and protein sequencing: as an analyte such as a peptide or protein traverses a nanos…
Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens
Konstantin Nikolaou, Sven Krippendorf, Samuel Tovey +1
Scaling laws offer valuable insights into the relationship between neural network performance and computational cost, yet their underlying mechanisms remain poorly understood. In t…
Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials
Moritz René Schäfer, Nico Segreto, Fabian Zills +2
We introduce Atomistic learned potentials in JAX (apax), a flexible and efficient open source software package for training and inference of machine-learned interatomic potentials.…