Code for Machine Learning for Algorithmic Trading, 2nd edition.
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Updated
Jun 21, 2023 - Jupyter Notebook
Code for Machine Learning for Algorithmic Trading, 2nd edition.
Synthetic Patient Population Simulator
A procedural Blender pipeline for photorealistic training image generation
UnrealCV: Connecting Computer Vision to Unreal Engine
Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.
Synthetic data generation for tabular data
Conditional GAN for generating synthetic tabular data.
Synthetic data generators for tabular and time-series data
This repository contains the collection of UCI (real-life) datasets and Synthetic (artificial) datasets (with cluster labels and MATLAB files) ready to use with clustering algorithms.
🟣 Object detection of abstract shapes with neural networks
A library to model multivariate data using copulas.
The Declarative Data Generator
Generative adversarial training for generating synthetic tabular data.
Synthetic data generators for structured and unstructured text, featuring differentially private learning.
Synthetic Minority Over-Sampling Technique for Regression
Code used to generate synthetic scenes and bounding box annotations for object detection. This was used to generate data used in the Cut, Paste and Learn paper
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
Learn to map surrounding vehicles onto a bird's eye view of the scene.
[ICML 2023] The official implementation of the paper "TabDDPM: Modelling Tabular Data with Diffusion Models"
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