Python Decision-models-optimization Resources

pyrelational is a python active learning library developed by Relation Therapeutics for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.

MOEA-HH An open-source hyper-heuristic framework for multi-objective optimization. Introduction The multi-objective optimization technique is widely u

This is a salary prediction website developed with the help of machine learning, this makes prediction of salary on basis of few parameters like interview score, experience test score.

Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces" This repo contains the implementation of GEBO algorithm.

Posterior temperature optimized Bayesian models for inverse problems in medical imaging Max-Heinrich Laves*, Malte Tölle*, Alexander Schlaefer, Sandy

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

Graph Convolution Simulator (GCS) Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions" Requirements: PyTor

Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation This reposi

Fliscopt FLIght SCheduling OPTimization 🛫 or fliscopt is a simple optimization library for flight scheduling and related problems in the discrete dom

ES_OTN_Public Carlos Güemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn

Current gate-based quantum computers have the potential to provide a computational advantage if algorithms use quantum hardware efficiently.

Event Queue Dialect Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure. Motivation The m

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

Source code for EquiDock: Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (ICLR 2022) Please cite "Independent SE(3)-Equivar

An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make

Hybrid Machine learning Model Clone the Repository Create a new Directory as assests and download the model from the below link Model Link To Start th

Tensorflow2 Keras-based Semantic Segmentation Models Implementation

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.

Crypto Portfolio Clustering Crypto Portfolio Clustering with and without optimization techniques (elbow method, PCA). Analysis This is an anlysis of c

NLP-Summarizer Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5 This project aimed to provide in

Probabilistic U-Net + **Update** + An improved Model (the Hierarchical Probabilistic U-Net) + LIDC crops is now available. See below. Re-implementatio

Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a

Generative Deep Art A curated list of Generative Deep Art projects, tools, artworks, and models Inbox Get started with making AI art in 2022 – deeplea

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

Automating reinforcement learning architecture design for code optimization. Che

QVC Optimizer Review Code for the paper "An Empirical Review of Optimization Techniques for Quantum Variational Circuits". Each of the python files ca

RRT-Algorithm-Visualisation This is a project that aims to develop upon the RRT

Brain Weight in Humans Variations of head sizes and brain weights in humans Kaggle dataset obtained from this link by Anubhab Swain. Image obtained fr

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

A transformer that does not hog your GPU memory This is an early in-development codebase: if you want a stable and documented hivemind codebase, look

Tutorial on Amortized Optimization This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize

Constrained Language Models Yield Few-Shot Semantic Parsers This repository contains tools and instructions for reproducing the experiments in the pap

GoldNanoparticles This GitHub repo consists of Code and Some results of project- Diabetes Treatment using Gold nanoparticles. These Consist of ML Mode

TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi

spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t

LINUX-AOS (Automatic Optimization System)

GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear

Transformers are all you need In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a

Variational DiffWave Training DiffWave using variational method from Variational Diffusion Models. Quick Start python train_distributed.py discrete_10

DART Implementation for ICLR2022 paper Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Environment [email protected] Use pi

BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库，帮助大家挑选或训练出更适合自己科研或者业务的模型结构。 文档地址：https://basecls.readthedocs.io 安装 安装环境 BaseCls 需要 Python = 3.6。 BaseCls 依赖 M

An implementation of the Fibonacci method for gradient descent, featuring a TKinter GUI for inputting the function / parameters to be examined and a matplotlib plot of the function and results.

DecisionTransformer_StepbyStep Intro Decision Transformer: A brand new Offline RL Pattern. 这是关于NeurIPS 2021 热门论文Decision Transformer的复现。 👍 原文地址: Deci

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce

NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,

smc.covid smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectiou

User-centered Regression An Approach to Explore Logistic Regression Models This tool applies the potential of Attribute-RadViz in identifying correlat

Approximate Multiplier by HEAM What's HEAM? HEAM is a general optimization method to generate high-efficiency approximate multipliers for specific app

ReLSO Improved Fitness Optimization Landscapes for Sequence Design Description Citation How to run Training models Original data source Description In

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un

AI for TSP Competition Goal In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted

How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis

Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization This repository contains the code for the BBI optimizer, introduced in the p

Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W

This repository contains Pytorch evaluation code, training code and pretrained models for the following projects: SPACH (A Battle of Network Structure

shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t

The purpose of this project is create a predictive model capable of identifying the probability of a person securing an admit based on their personal profile parameters. Simplified visualisations have been created for understanding the data. 80% accuracy was achieved on the test set.

Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin

Twitter-News-Summarizer Twitter bot that uses NLP models to summarize news articles referenced in a user's twitter timeline 1.) Extracts all tweets fr

OptiPLANT OptiPLANT is a cloud-based based system that empowers professional and non-professional data scientists to build high-quality predictive mod

In this project it was used some different Machine Learning models to identify the gender of a voice (Female or Male) based on some specific speech and voice attributes.

GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language

Contriever: Towards Unsupervised Dense Information Retrieval with Contrastive Learning This repository contains pre-trained models and some evaluation

TweebankNLP This repo contains the new Tweebank-NER dataset and off-the-shelf Twitter-Stanza pipeline for state-of-the-art Tweet NLP, as described in

SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti

On Out-of-distribution Detection with Energy-based Models This repository contains the code for the experiments conducted in the paper On Out-of-distr

Mixture of Volumetric Primitives -- Training and Evaluation This repository contains code to train and render Mixture of Volumetric Primitives (MVP) m

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali

Boltzmann visualization - Visualize the Boltzmann distribution for simple quantum models of molecular motion

f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation [Paper] [PyTorch] [MXNet] [Video] This repository provides code for training

BERTopic BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable

COVID-ViT COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models This code is to response to te MIA-COV19 compe

Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of

Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl

Deep learning for Earth Observation This repository contains code, network definitions and pre-trained models for working on remote sensing images usi

A collection of semantic image segmentation models implemented in TensorFlow. Contains data-loaders for the generic and medical benchmark datasets.

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

Creating Multi Task Models With Keras About The Project! I used the keras and Tensorflow Library, To build a Deep Learning Neural Network to Creating

Diabetes Prediction Using Decision Tree Introduction Decision tree is the most powerful and popular tool for classification and prediction. A Decision

Tools for mathematical optimization region

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.

Feature engineering and machine learning: together at last! Lambdo is a workflow engine which significantly simplifies data analysis by unifying featu

Decision Weights in Prospect Theory It's clear that humans are irrational, but how irrational are they? After some research into behavourial economics

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

ocrd_detectron2 OCR-D wrapper for detectron2 based segmentation models Introduction Installation Usage OCR-D processor interface ocrd-detectron2-segm

Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee

Pre-trained models based on TensorLayerX. TensorLayerX is a multi-backend AI fra

Decision-Threshold-ML Tutorial for improve skills: 'Decision Threshold In Machine Learning' (from GeeksforGeeks) by Marcus Mariano For more informatio

Blackstone Blackstone is a spaCy model and library for processing long-form, unstructured legal text. Blackstone is an experimental research project f

MADT: Offline Pre-trained Multi-Agent Decision Transformer A link to our paper can be found on Arxiv. Overview Official codebase for Offline Pre-train

Official PyTorch implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 Spotlight Paper) Zhisheng

PyTorch Image Classification Following papers are implemented using PyTorch. ResNet (1512.03385) ResNet-preact (1603.05027) WRN (1605.07146) DenseNet

T‘rex Park is a Youzan sponsored project. Offering Chinese NLP and image models pretrained from E-commerce datasets (product titles, images, comments, etc.).

TweebankNLP This repo contains the new Tweebank-NER dataset and Twitter-Stanza p

ColossalAI-Examples This repository contains examples of training models with Co