Research

 PUBLICATIONS

Journal Publications

Papillon, M.*, Sanborn, S.*, Mathe, J.*, Cornelis, L.*, Bertics, A., …, Miolane, N. "Beyond Euclid: an illustrated guide to modern machine learning with geometric, topological, and algebraic structures." Machine Learning: Science and Technology 6.3 (2025): 031002.

Under Review

Bertics, A., Chrastil, E., Miolane, N., Carlson, J. “Flow Tree: A model for navigator dynamics and environmental complexity.” Under review at Journal of the Royal Society Interface. 

In Progress

Bertics, A.*, Dinc, F.*, Kurtkaya, B., Yuan, P., Miolane, N. “Parameter identifiability and preserved dynamics in RNN models of neural computations.” In progress.

Bertics, A., Chrastil, E., Carlson, J. “Dynamic signatures of collective navigation in a network with semantic

structure.” In progress. 

Calissano, A.,  Bertics, A., Pereira, L., Lueg, J., Miolane, N. “On the Implementation of Geodesic Metric Spaces.” In progress.

Acosta, F., Bertics, A., …, Miolane, N. “When are Intrinsic Timescales Mechanistically Meaningful in Recurrent Neural Networks?” In progress. 

 CONFERENCE PRESENTATIONS

Talks

Bertics, A. and Pereira, L. “Geometry and dynamics in learning.” SIAM: WiMSoCal (2026). 

Posters

Bertics, A.*, Dinc, F.*, Kurtkaya, B., Miolane, N. “Parameter identifiability and preserved dynamics in data-constrained recurrent neural networks.” Society for Neuroscience (2025).

Bertics, A., Chrastil, E., Miolane, N., Carlson, J. "Flow Tree: A dynamical classifier for quantifying navigation paths and strategies." Computational and Systems Neuroscience (2024).

Projects