An Empirical Review of Optimization Techniques for Quantum Variational Circuits

Related tags

Deep Learning Model Explanationqvc_opt_review
Overview

QVC Optimizer Review

Code for the paper "An Empirical Review of Optimization Techniques for Quantum Variational Circuits".

Each of the python files can be run and will generate the results for the associated set of problem setups. To enable/disable noise, comment out or uncomment the only line that has the .with_noise(cirq.depolarize(p=0.01)).

All the results are available in the results.txt organized by task, score, and standard deviation over the 3 runs.

Open Call For Research

Check out the CONTRIBUTING.md and take on one of the issues (or make your own). For more information, see the video:

Owner
Owen Lockwood
Owen Lockwood
GitHub Repository
Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮

Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮

Datature 243 Jan 05, 2023
Lime: Explaining the predictions of any machine learning classifier

lime This project is about explaining what machine learning classifiers (or models) are doing. At the moment, we support explaining individual predict

Marco Tulio Correia Ribeiro 10.3k Jan 01, 2023
A library for debugging/inspecting machine learning classifiers and explaining their predictions

ELI5 ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. It provides support for the following m

2.6k Dec 30, 2022
Auralisation of learned features in CNN (for audio)

AuralisationCNN This repo is for an example of auralisastion of CNNs that is demonstrated on ISMIR 2015. Files auralise.py: includes all required func

Keunwoo Choi 39 Nov 19, 2022
An intuitive library to add plotting functionality to scikit-learn objects.

Welcome to Scikit-plot Single line functions for detailed visualizations The quickest and easiest way to go from analysis... ...to this. Scikit-plot i

Reiichiro Nakano 2.3k Dec 31, 2022
Convolutional neural network visualization techniques implemented in PyTorch.

This repository contains a number of convolutional neural network visualization techniques implemented in PyTorch.

1 Nov 06, 2021
A library that implements fairness-aware machine learning algorithms

Themis ML themis-ml is a Python library built on top of pandas and sklearnthat implements fairness-aware machine learning algorithms. Fairness-aware M

Niels Bantilan 105 Dec 30, 2022
Visualizer for neural network, deep learning, and machine learning models

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens

Lutz Roeder 20.9k Dec 28, 2022
PyTorch implementation of DeepDream algorithm

neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br

121 Nov 05, 2022
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).

GNNLens2 is an interactive visualization tool for graph neural networks (GNN).

Distributed (Deep) Machine Learning Community 143 Jan 07, 2023
Net2Vis automatically generates abstract visualizations for convolutional neural networks from Keras code.

Automatic neural network visualizations generated in your browser!

Visual Computing Group (Ulm University) 99 Nov 30, 2022
Lucid library adapted for PyTorch

Lucent PyTorch + Lucid = Lucent The wonderful Lucid library adapted for the wonderful PyTorch! Lucent is not affiliated with Lucid or OpenAI's Clarity

Lim Swee Kiat 520 Dec 26, 2022
A ultra-lightweight 3D renderer of the Tensorflow/Keras neural network architectures

A ultra-lightweight 3D renderer of the Tensorflow/Keras neural network architectures

Souvik Pratiher 16 Nov 17, 2021
Visual analysis and diagnostic tools to facilitate machine learning model selection.

Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual

District Data Labs 3.9k Dec 30, 2022
treeinterpreter - Interpreting scikit-learn's decision tree and random forest predictions.

TreeInterpreter Package for interpreting scikit-learn's decision tree and random forest predictions. Allows decomposing each prediction into bias and

Ando Saabas 720 Dec 22, 2022
Quickly and easily create / train a custom DeepDream model

Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat

56 Jan 03, 2023
A python library for decision tree visualization and model interpretation.

dtreeviz : Decision Tree Visualization Description A python library for decision tree visualization and model interpretation. Currently supports sciki

Terence Parr 2.4k Jan 02, 2023
A Practical Debugging Tool for Training Deep Neural Networks

Cockpit is a visual and statistical debugger specifically designed for deep learning!

31 Aug 14, 2022
Interpretability and explainability of data and machine learning models

AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase

1.2k Dec 29, 2022
Pytorch Feature Map Extractor

MapExtrackt Convolutional Neural Networks Are Beautiful We all take our eyes for granted, we glance at an object for an instant and our brains can ide

Lewis Morris 40 Dec 07, 2022