NMA Computational Neuroscience course
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Updated
May 23, 2024 - Jupyter Notebook
NMA Computational Neuroscience course
Kalman Filter implementation in Python using Numpy only in 30 lines.
Notes on topics ranging from Recurrent Newtorks to Automatic Control and Reinforcement Learning
Robust control for dynamic nonlinear systems with parameter uncertainties
ODESCA is a MATLAB tool for the creation and analysis of dynamic systems described by ordinary differential equations
Package primarily for simulation of the MAT model
Modelling crowd behaviour in panic sitations
Implements the algorithm introduced in our paper: Temporal Logic Explanations for Dynamic Decision Systems using Anchors and Monte Carlo Tree Search
An Animation-Interpolator, "reverse-engineered" from facebook/rebound
Granger Causality with Signal-dependent Noise
Real time parameter estimation on Grey Box Dynamic Systems
Here, I include my thoughts about how does the brain of the worm give rise to remarkable behavioral plasticities
Pytorch implementation of Stable Vector Fields on Lie Groups through Diffeomorphism
Introduction to analyze piecewise-smooth systems using python
Descent into Chaos: An Exploration of Two Dynamical Systems
some matlab work and plotting stuff
Simulation environment which enables research on the properties of objects and physical systems described by linear and non-linear differential equations.
Computational model of the electromotor command network of pulse-type mormyrids.
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