Skip to main content

Ctrl+K

Quickstart

Installation
Simulating a Brain Dynamics Model
Training a Brain Dynamics Model
Analyzing a Brain Dynamics Model

BrainPy Core Concepts

Concept 1: Object-oriented Transformation
Concept 2: Dynamical System

Brain Dynamics Tutorials

Math Foundation
Model Building
Model Simulation
- Simulation with DSRunner
- Parallel Simulation for Parameter Exploration
Model Training
Model Analysis

Advanced Tutorials

How does low-dimensional analyzers work?
Interoperation with other JAX frameworks

Toolboxes

Numerical Solvers for Ordinary Differential Equations
Numerical Solvers for Stochastic Differential Equations
Numerical Solvers for Fractional Differential Equations
Numerical Solvers for Delay Differential Equations
Joint Differential Equations
Synaptic Connections
Synaptic Weights
Gradient Descent Optimizers
Saving and Loading
Inputs Construction

Frequently Asked Questions

How to cite BrainPy?
How is brainpy different from other frameworks?
BrainPy Ecosystem for Brain Dynamics Modeling

API Documentation

brainpy module
brainpy.math module
brainpy.channels module
brainpy.layers module
brainpy.neurons module
brainpy.rates module
brainpy.synapses module
brainpy.synouts module
brainpy.synplast module
- brainpy.synplast.STD
- brainpy.synplast.STP
brainpy.integrators module
brainpy.analysis module
brainpy.connect module
brainpy.encoding module
brainpy.initialize module
brainpy.inputs module
brainpy.losses module
brainpy.measure module
brainpy.optim module
brainpy.running module
Release notes (brainpy)

.rst

brainpy.losses.mean_square

Contents

mean_square()

brainpy.losses.mean_square#

brainpy.losses.mean_square(predicts, axis=None)[source]#

previous

brainpy.losses.mean_absolute

next

brainpy.losses.log_cosh

Contents

mean_square()

By BrainPy Team

© Copyright 2020-2023, BrainPy.

Last updated on Aug 13, 2023.