Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. - Stefan Horoi; Victor Geadah; Guy Wolf; Guillaume Lajoie (Canadian AI, 2020)

Advantages of biologically-inspired adaptive neural activation in RNNs during learning. - Victor Geadah; Giancarlo Kerg; Stefan Horoi; Guy Wolf; Guillaume Lajoie (CoRR, 2020)

Inferring System and Optimal Control Parameters of Closed-Loop Systems from Partial Observations. - Victor Geadah; Juncal Arbelaiz; Harrison Ritz; Nathaniel D. Daw; Jonathan D. Cohen 003; Jonathan W. Pillow (CDC, 2024)

Parsing neural dynamics with infinite recurrent switching linear dynamical systems. - Victor Geadah; International Brain Laboratory; Jonathan W. Pillow (ICLR, 2024)

Sparse-Coding Variational Autoencoders. - Victor Geadah; Gabriel Barello; C. Daniel Greenidge; Adam S. Charles; Jonathan W. Pillow (Neural Comput., 2024)

Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization. - Victor Geadah; Stefan Horoi; Giancarlo Kerg; Guy Wolf; Guillaume Lajoie (PLoS Comput. Biol., 2024)

Comparing noisy neural population dynamics using optimal transport distances. - Amin Nejatbakhsh; Victor Geadah; Alex H. Williams; David Lipshutz (ICLR, 2025)