Parameter-ensemble-differential-evolution - Shows how to do parameter ensembling using differential evolution.

Related tags

Deep Learningparameter-ensemble-differential-evolution
Overview

Ensembling parameters with differential evolution

This repository shows how to ensemble parameters of two trained neural networks using differential evolution. The steps followed are as follows:

  • Train two networks (architecturally same) on the same dataset (CIFAR-10 used here) but from two different random initializations.

  • Ensemble their weights using the following formulae:

    w_t = w_o * ema + (1 - ema) * w_p

    w_o and w_p represents the learned of a neural network.

  • Randomly initialize a network (same architecture as above) and populate its parameters w_t using the above formulae.

ema is usually chosen by the developer in an empirical manner. This project uses differential evolution to find it.

Below are the top-1 accuracies (on CIFAR-10 test set) of two individually trained two models along with their ensembled variant:

  • Model one: 63.23%
  • Model two: 63.42%
  • Ensembled: 63.35%

With the more conventional average prediction ensembling, I was able to get to 64.92%. This is way better than what I got by ensembling the parameters. Nevertheless, the purpose of this project was to just try out an idea.

Reproducing the results

Ensure the requirements.txt is satisfied. Then train two models with ensuring your working directory is at the root of this project:

$ git clone https://github.com/sayakpaul/parameter-ensemble-differential-evolution
$ cd parameter-ensemble-differential-evolution
$ pip install -qr requirements.txt
$ for i in `seq 1 2`; python train.py; done

Then just follow the ensemble-parameters.ipynb notebook. You can also use the networks I trained. Instructions are available inside the notebook.

References

You might also like...
Neural Ensemble Search for Performant and Calibrated Predictions
Neural Ensemble Search for Performant and Calibrated Predictions

Neural Ensemble Search Introduction This repo contains the code accompanying the paper: Neural Ensemble Search for Performant and Calibrated Predictio

AutoML-Freiburg-Hannover 26 Dec 12, 2022
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

null 0 May 6, 2022
zeus is a Python implementation of the Ensemble Slice Sampling method.
zeus is a Python implementation of the Ensemble Slice Sampling method.

zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl

Minas Karamanis 197 Dec 4, 2022
Pytorch implementation of SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation
Pytorch implementation of SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation

SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation Efficient Self-Ensemble Framework for Semantic Segmentation by Walid Bousselham

null 61 Dec 26, 2022
Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning
Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning

Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning This repository is official Tensorflow implementation of paper: Ensemb

Seunghyun Lee 12 Oct 18, 2022
This Jupyter notebook shows one way to implement a simple first-order low-pass filter on sampled data in discrete time.

How to Implement a First-Order Low-Pass Filter in Discrete Time We often teach or learn about filters in continuous time, but then need to implement t

Joshua Marshall 4 Aug 24, 2022
A fast Evolution Strategy implementation in Python

Evostra: Evolution Strategy for Python Evolution Strategy (ES) is an optimization technique based on ideas of adaptation and evolution. You can learn

Mika 251 Dec 8, 2022
Code for the paper Task Agnostic Morphology Evolution.

Task-Agnostic Morphology Optimization This repository contains code for the paper Task-Agnostic Morphology Evolution by Donald (Joey) Hejna, Pieter Ab

Joey Hejna 18 Aug 4, 2022
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

flownet2-pytorch Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. Multiple GPU training is supported, a

NVIDIA Corporation 2.8k Dec 27, 2022
Releases(v0.1.0)
Owner
Sayak Paul
Trying to learn how machines learn.
Sayak Paul
GitHub Repository
Automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azure

fwhr-calc-website This project is to automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azur

SoohyunPark 1 Feb 07, 2022
Assginment for UofT CSC420: Intro to Image Understanding

Run the code Open edge_detection.ipynb in google colab. Upload image1.jpg,image2.jpg and my_image.jpg to '/content/drive/My Drive'. chooose 'Run all'

Ziyi-Zhou 1 Feb 24, 2022
Code for paper: Towards Tokenized Human Dynamics Representation

Video Tokneization Codebase for video tokenization, based on our paper Towards Tokenized Human Dynamics Representation. Prerequisites (tested under Py

Kenneth Li 20 May 31, 2022
Python Actor concurrency library

Thespian Actor Library This library provides the framework of an Actor model for use by applications implementing Actors. Thespian Site with Documenta

Kevin Quick 177 Dec 11, 2022
This repository contains the map content ontology used in narrative cartography

Narrative-cartography-ontology This repository contains the map content ontology used in narrative cartography, which is associated with a submission

Weiming Huang 0 Oct 31, 2021
DLL: Direct Lidar Localization

DLL: Direct Lidar Localization Summary This package presents DLL, a direct map-based localization technique using 3D LIDAR for its application to aeri

Service Robotics Lab 127 Dec 16, 2022
Multi-Scale Geometric Consistency Guided Multi-View Stereo

ACMM [News] The code for ACMH is released!!! [News] The code for ACMP is released!!! About ACMM is a multi-scale geometric consistency guided multi-vi

Qingshan Xu 118 Jan 04, 2023
An updated version of virtual model making

Model-Swap-Face v2   这个项目是基于stylegan2 pSp制作的，比v1版本Model-Swap-Face在推理速度和图像质量上有一定提升。主要的功能是将虚拟模特进行环球不同区域的风格转换，目前转换器提供西欧模特、东亚模特和北非模特三种主流的风格样式，可帮我们实现生产资料零成

seeprettyface.com 62 Dec 09, 2022
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

Aitor Ruano 87 Dec 16, 2022
git《Self-Attention Attribution: Interpreting Information Interactions Inside Transformer》(AAAI 2021) GitHub:

Self-Attention Attribution This repository contains the implementation for AAAI-2021 paper Self-Attention Attribution: Interpreting Information Intera

60 Dec 29, 2022
Vision Transformer for 3D medical image registration (Pytorch).

ViT-V-Net: Vision Transformer for Volumetric Medical Image Registration keywords: vision transformer, convolutional neural networks, image registratio

Junyu Chen 192 Dec 20, 2022
Implements Stacked-RNN in numpy and torch with manual forward and backward functions

Recurrent Neural Networks Implements simple recurrent network and a stacked recurrent network in numpy and torch respectively. Both flavours implement

Vishal R 1 Nov 16, 2021
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage

Keepsake Version control for machine learning. Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Goo

Replicate 1.6k Dec 29, 2022
Deep and online learning with spiking neural networks in Python

Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern

Jason Eshraghian 447 Jan 03, 2023
Python implementation of "Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation"

MIPNet: Multi-Instance Pose Networks This repository is the official pytorch python implementation of "Multi-Instance Pose Networks: Rethinking Top-Do

Rawal Khirodkar 57 Dec 12, 2022
LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021

LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021 We propose a cross encoder model (LTR_CrossEncoder) for information retrieval, re-retrie

Xuan Hieu Duong 7 Jan 12, 2022
Real-time pose estimation accelerated with NVIDIA TensorRT

trt_pose Want to detect hand poses? Check out the new trt_pose_hand project for real-time hand pose and gesture recognition! trt_pose is aimed at enab

NVIDIA AI IOT 803 Jan 06, 2023
High-Resolution Image Synthesis with Latent Diffusion Models

Latent Diffusion Models Requirements A suitable conda environment named ldm can be created and activated with: conda env create -f environment.yaml co

CompVis Heidelberg 5.6k Jan 04, 2023
Efficient and intelligent interactive segmentation annotation software

Efficient and intelligent interactive segmentation annotation software

294 Dec 30, 2022
Selfplay In MultiPlayer Environments

This project allows you to train AI agents on custom-built multiplayer environments, through self-play reinforcement learning.

200 Jan 08, 2023