An Empirical Review of Optimization Techniques for Quantum Variational Circuits

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
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.

Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The

Benedek Rozemberczki 187 Dec 27, 2022
Algorithms for monitoring and explaining machine learning models

Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual

Seldon 1.9k Dec 30, 2022
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
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.

Jacob Gildenblat 6.5k Jan 01, 2023
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
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic

Chandan Singh 111 Jan 03, 2023
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 game theoretic approach to explain the output of any machine learning model.

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo

Scott Lundberg 18.3k Jan 08, 2023
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
🎆 A visualization of the CapsNet layers to better understand how it works

CapsNet-Visualization For more information on capsule networks check out my Medium articles here and here. Setup Use pip to install the required pytho

Nick Bourdakos 387 Dec 06, 2022
Implementation of linear CorEx and temporal CorEx.

Correlation Explanation Methods Official implementation of linear correlation explanation (linear CorEx) and temporal correlation explanation (T-CorEx

Hrayr Harutyunyan 34 Nov 15, 2022
Logging MXNet data for visualization in TensorBoard.

Logging MXNet Data for Visualization in TensorBoard Overview MXBoard provides a set of APIs for logging MXNet data for visualization in TensorBoard. T

Amazon Web Services - Labs 327 Dec 05, 2022
Interactive convnet features visualization for Keras

Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis

Keplr 1.7k Dec 21, 2022
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
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
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
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.

ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi

ModelChimp 124 Dec 21, 2022
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
Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Hendrik Strobelt 1.1k Jan 04, 2023
Code for "High-Precision Model-Agnostic Explanations" paper

Anchor This repository has code for the paper High-Precision Model-Agnostic Explanations. An anchor explanation is a rule that sufficiently “anchors”

Marco Tulio Correia Ribeiro 735 Jan 05, 2023