Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras

Overview

neural_calibrator

Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals. I dont think this is great code but i think that is something for people to start with and works for my use case.

currently supports:

  • CoxIngersollRoss Process
  • Diffusion Process
  • Fractional Brownian Motion
  • Geometric Brownian Motion
  • Ornstein Uhlenbeck Process
  • Poisson Process
  • Vasicek Process

what's what:

- data_generation.py -> handles data (sample, config, saving to csv for post analysis, train/test split, ...)
- main.py -> this is where you f5 and follow instructions to get the trained .h5 model to load elsewhere
- network.py -> basically the network we'll train, test and save if needed. kept as clean as possible so you can copy/paste most of this elsewhere.
- network_manager.py -> handles the actual heavy stuff like training/testing/tensorboard/etc. made for extension but not much work put into it.
- start_here.ipynb -> small notebook with examples

comming up next:

  • Markov chains (HMM/Bernoulli chains/etc)
  • Hawkes process
Owner
Federico Lopez
sic transit gloria mundi
Federico Lopez
Matlab Python Heuristic Battery Opt - SMOP conversion and manual conversion

SMOP is Small Matlab and Octave to Python compiler. SMOP translates matlab to py

Tom Xu 1 Jan 12, 2022
Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.

Population-Based Bandits (PB2) Code for the Population-Based Bandits (PB2) Algorithm, from the paper Provably Efficient Online Hyperparameter Optimiza

Jack Parker-Holder 22 Nov 16, 2022
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network

SynSense 21 Dec 14, 2022
Official implementation for the paper: Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Generating Smooth Pose Sequences for Diverse Human Motion Prediction This is official implementation for the paper Generating Smooth Pose Sequences fo

Wei Mao 28 Dec 10, 2022
Official Pytorch implementation of Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations

Scene Representation Networks This is the official implementation of the NeurIPS submission "Scene Representation Networks: Continuous 3D-Structure-Aw

Vincent Sitzmann 365 Jan 06, 2023
DanceTrack: Multiple Object Tracking in Uniform Appearance and Diverse Motion

DanceTrack DanceTrack is a benchmark for tracking multiple objects in uniform appearance and diverse motion. DanceTrack provides box and identity anno

260 Dec 28, 2022
New AidForBlind - Various Libraries used like OpenCV and other mentioned in Requirements.txt

AidForBlind Recommended PyCharm IDE Various Libraries used like OpenCV and other

Aalhad Chandewar 1 Jan 13, 2022
Implementation of Monocular Direct Sparse Localization in a Prior 3D Surfel Map (DSL)

DSL Project page: https://sites.google.com/view/dsl-ram-lab/ Monocular Direct Sparse Localization in a Prior 3D Surfel Map Authors: Haoyang Ye, Huaiya

Haoyang Ye 93 Nov 30, 2022
Code & Data for Enhancing Photorealism Enhancement

Code & Data for Enhancing Photorealism Enhancement

Intel ISL (Intel Intelligent Systems Lab) 1.1k Jan 08, 2023
Official PyTorch Implementation of Rank & Sort Loss [ICCV2021]

Rank & Sort Loss for Object Detection and Instance Segmentation The official implementation of Rank & Sort Loss. Our implementation is based on mmdete

Kemal Oksuz 229 Dec 20, 2022
Code for the SIGGRAPH 2021 paper "Consistent Depth of Moving Objects in Video".

Consistent Depth of Moving Objects in Video This repository contains training code for the SIGGRAPH 2021 paper "Consistent Depth of Moving Objects in

Google 203 Jan 05, 2023
Prevent `CUDA error: out of memory` in just 1 line of code.

🐨 Koila Koila solves CUDA error: out of memory error painlessly. Fix it with just one line of code, and forget it. 🚀 Features 🙅 Prevents CUDA error

RenChu Wang 1.7k Jan 02, 2023
Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2

Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot

Phil Wang 97 Dec 28, 2022
AirLoop: Lifelong Loop Closure Detection

AirLoop This repo contains the source code for paper: Dasong Gao, Chen Wang, Sebastian Scherer. "AirLoop: Lifelong Loop Closure Detection." arXiv prep

Chen Wang 53 Jan 03, 2023
一个多语言支持、易使用的 OCR 项目。An easy-to-use OCR project with multilingual support.

AgentOCR 简介 AgentOCR 是一个基于 PaddleOCR 和 ONNXRuntime 项目开发的一个使用简单、调用方便的 OCR 项目 本项目目前包含 Python Package 【AgentOCR】 和 OCR 标注软件 【AgentOCRLabeling】 使用指南 Pytho

AgentMaker 98 Nov 10, 2022
A framework for attentive explainable deep learning on tabular data

🧠 kendrite A framework for attentive explainable deep learning on tabular data 💨 Quick start kedro run 🧱 Built upon Technology Description Links ke

Marnix Koops 3 Nov 06, 2021
Özlem Taşkın 0 Feb 23, 2022
Pytorch code for our paper "Feedback Network for Image Super-Resolution" (CVPR2019)

Feedback Network for Image Super-Resolution [arXiv] [CVF] [Poster] Update: Our proposed Gated Multiple Feedback Network (GMFN) will appear in BMVC2019

Zhen Li 539 Jan 06, 2023
MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.

Documentation | FAQ | Release Notes | Roadmap | MACE Model Zoo | Demo | Join Us | 中文 Mobile AI Compute Engine (or MACE for short) is a deep learning i

Xiaomi 4.7k Dec 29, 2022
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

Deep Reinforcement Learning Agents This repository contains a collection of reinforcement learning algorithms written in Tensorflow. The ipython noteb

Arthur Juliani 2.2k Jan 01, 2023