adityagilra Goto Github PK

2015_spiking_population_response

Calculate and plot response of a population of spiking neurons to a constant and a sinusoid riding on top via simulation (brian2) and theory (integral and differential approaches); uses my neurtheor module.

archibrain

Synthesize bio-plausible neural networks for cognitive tasks, mimicking brain architecture

beliefstaterl

biologicallyplausiblelearningrnn

ddpg-pytorch

Deep Deterministic Policy Gradient implemented in PyTorch for DeepMind Control Suite

follow

Feedback-based Online Local Learning Of Weights (FOLLOW)

followcontrol

Motor control using inverse model learned via FOLLOW

from-papers

Notes / derivations / models from papers that I have read since April 2014.

gym

A toolkit for developing and comparing reinforcement learning algorithms.

isca

Idealized GCM from the University of Exeter

meld

MELD: Meta-Reinforcement Learning from Images via Latent State Models https://arxiv.org/abs/2010.13957

nengo

A Python library for creating and simulating large-scale brain models

nengo_mpi

MPI backend for the nengo neural simulator.

nengo_ocl

OpenCL-based simulator for Nengo neural models

neurtheor

NeuroTheory: A Python module to compute baseline and linear response of populations of spiking neurons in the integral or differential framework. See Gerstner et al book [ http://neuronaldynamics.epfl.ch/ ] for the spike response model of neurons and related integral approach. See Richardson 2007 [ http://link.aps.org/doi/10.1103/PhysRevE.76.021919 ] for the differential approach on the LIF model.

olfactory-bulb

A detailed network model of part of the rat olfactory bulb comprising compartmental mitral, granule and PG cells developed by Aditya Gilra and Upinder S. Bhalla (Gilra A, Bhalla US (2015) Bulbar Microcircuit Model Predicts Connectivity and Roles of Interneurons in Odor Coding. PLoS ONE 10(5): e0098045.) The cell morphologies and network connections are in NeuroML v1.8.

pfc_md_weights_stability

pynn

A Python package for simulator-independent specification of neuronal network models.

ratesimulator

Simple python simulator for 'rate neurons' with continuous-valued, rectified output, connected by static/plastic synapses.

rcesn_spatio_temporal

Spatio-temporal forecasting of Lorenz96 with RC-ESN, RNN-LSTM and ANN

simple-a2c

A simple A2C made from scratch in PyTorch. Accompanying comic at https://hackernoon.com/intuitive-rl-intro-to-advantage-actor-critic-a2c-4ff545978752

spinningup

An educational resource to help anyone learn deep reinforcement learning.

studywolf_control

A repository for control benchmarking code

treehmm-local

Provided is the code and accompanying documentation for inferring the parameters (via the Baum-Welch algorithm; see Prentice et al., 2016) of the Tree hidden Markov model (HMM) for neural population spike train data. This version can be used locally directly in Matlab, via mex files, or in Python via `make` using the Makelfile..

tutorials

Tutorials that I've given as a tutor at computational neuroscience summer schools

unsupervisedlearningneuraldata

Finding or learning latent modes / clusters in neural spiking data

viwta-snn

Implementation in C++ (mexed for local callable use in Matlab, now in Python too) of the variational inference winner-take-all neural circuit model for real-time unsupervised clustering.