An ongoing collection of ipython notebooks and interactive visualizations on neuroscience, machine learning & computer science from xcorr: computational neuroscience.
By Patrick Mineault, PhD
- ICA with normalizing flow models (NICE)
- PCA through gradient descent
- Gibbs sampling & block Gibbs sampling for the Ising model
- Persistent contrastive divergence for maximum entropy models
- Contextual bandits with Thompson sampling
- Q-Learning in OpenAI gym
- Multi-armed bandit as a Markov decision process
- Second order Wiener-Volterra estimation
- Reduced variance in reverse correlation estimates, antithetic sampling
- Polynomial regression vs. Taylor expansion
- Linear integrate-and-fire neurons
- Networks of balanced E/I linear integrate-and-fire neurons
- A scrollytelling tour of balanced E/I networks
- Optimal control with a linear quadratic regulator
- Stabilizing the cart pole with control theory
- Self-organized criticality: the forest fire model
- RGB color mixing
- Nonlinear feedback to decouple network of oscillators