---
date: 2020-08-28
excerpts: 2
---

# Motivic information, path integrals and spiking networks

I'm writing a series of posts that will explore the connections between these topics. Here is a rough outline of the series, which I will fill in slowly over time.

## Motivic Information

1. [Building foundations of information theory on relative information](2020-09-08-building-foundations-of-information-theory-on-relative-information/)
2. [Conditional relative information and its axiomizations](2020-09-18-conditional-relative-information-and-its-axiomatizations/)
3. [Zeta functions, Mellin transforms and the Gelfand-Leray form](2020-10-05-zeta-functions-mellin-transforms-and-the-gelfand-leray-form/)
4. [Motivic relative information](2020-10-07-motivic-relative-information/)

## Path Integrals

1. [Path integrals and continuous-time Markov chains](2020-10-14-path-integrals-and-continuous-time-markov-chains/)
2. [Biased stochastic approximation](2020-12-01-biased-stochastic-approximation/)

## Spiking Networks

1. [Machine learning with relative information](2020-10-23-machine-learning-with-relative-information/)
2. [Process learning with relative information](2021-03-21-process-learning-with-relative-information/)
3. [Relative inference for mutable processes](2021-03-22-relative-inference-with-mutable-processes/)
4. [Biased stochastic approximation for mutable processes](2021-03-23-biased-stochastic-approximation-with-mutable-processes/)
5. [Convergence of biased stochastic approximation](2021-06-01-convergence-of-biased-stochastic-approximation/)
6. [Spiking neural networks](2021-06-05-spiking-neural-networks/)