PierreOrhan
PhD Student at ENS, with JR King and Y. Boubenec. Previous work with A. Peyrache and K. Benchenane. Computational neuroscience
PierreOrhan's Stars
Sana3883/Scaling-up-Ridge
facebookresearch/dora
Dora is an experiment management framework. It expresses grid searches as pure python files as part of your repo. It identifies experiments with a unique hash signature. Scale up to hundreds of experiments without losing your sanity.
neurreps/awesome-neural-geometry
A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond
pymanopt/pymanopt
Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation
schung039/neural_manifolds_replicaMFT
mtsch/Ripserer.jl
Flexible and efficient persistent homology computation.
tachukao/mgplvm-pytorch
FatemehTarashi/awesome-tda
A curated list of topological data analysis (TDA) resources and links.
xjwanglab/book
CYHSM/awesome-neuro-ai-papers
Papers from the intersection of deep learning and neuroscience
gmarceaucaron/natural-langevin-dynamics-for-neural-networks
Code for reproducing experiments in the article "Gaétan Marceau Caron & Yann Ollivier, Natural Langevin Dynamics for Neural Networks (2017)"
mitmath/julia-mit
Tutorials and information on the Julia language for MIT numerical-computation courses.
SciML/DiffEqFlux.jl
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods