Mikkel Lepperød

V. Schøyen, M. B. Pettersen, K. Holzhausen, M. Fyhn, A. Malthe-Sørenssen and M. Lepperød

Coherently Remapping Toroidal Cells But Not Grid Cells are Responsible for Path Integration in Virtual Agents

iScience

M. Lepperød, T. Stöber, T. Hafting, M. Fyhn and K. Kording

Inferring causal connectivity from pairwise recordings and optogenetics

PLOS Computational Biology

S. Pontes-Filho, S. Nichele and M. Lepperød

Critical Neural Cellular Automata

Workshop "The Distributed Ghost Cellular Automata, Distributed Dynamical Systems, and Their Applications to Intelligence" at ALIFE 2023

M. Kvalsund, K. O. Ellefsen, K. Glette, S. Pontes-Filho and M. Lepperød

The distributed neocortex: How neuroscience can inspire distributed AI systems

Workshop "The Distributed Ghost Cellular Automata, Distributed Dynamical Systems, and Their Applications to Intelligence" at ALIFE 2023

K. Beshkov, J. Verhellen and M. Lepperød

Isometric Representations in Neural Networks Improve Robustness

arxiv

S. Nichele, S. Sæbø, K. Pettersen and M. Lepperød

NeuroAI - A strategic opportunity for Norway and Europe

Nordic Machine Intelligence

H. P. Targopula, A. Malthe-Sørenssen and M. Lepperød

Model-based meta reinforcement learning for alchemy

C. Bechkov, J. Verhellen and M. Lepperød

Manifold Propagation Through Neural Networks

M. B. Pettersen, V. Schøyen, A. Malthe-Sørenssen and M. Lepperød

Emergent Place Cells and Remapping in a Recurrent Neural Network Model

F. Rogge, A. Malthe-Sørenssen, M. Fyhn and M. Lepperød

On the Structural Sensitivity of the Successor Representation

C. Bechkov, J. Verhellen and M. Lepperød

Manifold propagation through recurrent neural networks

V. Schøyen, M. B. Pettersen, K. Holzhausen, A. Malthe-Sørenssen and M. Lepperød

Place and grid cell navigation in multiple environments

V. Schøyen, M. B. Pettersen, K. Holzhausen, A. Malthe-Sørenssen and M. Lepperød

Navigating Multiple Environments with Emergent Grid Cell Remapping

K. Holzhausen, M. Lepperød and A. Malthe-Sørenssen

Robustness of neural networks trained with biologically inspired local learning rules

I. Nymoen, F. Rogge, M. Lepperød, T. Hafting, K. K. Lensjø and M. Fyhn

Learning Flexibility in Parahippocampal Networks