Python Optimization-Planning-for-3D-ConvNets Resources

Path Planning using Neural A* Search (ICML 2021) This is a repository for the following paper: Ryo Yonetani*, Tatsunori Taniai*, Mohammadamin Barekata

Planning with Diffusion Training and visualizing of diffusion models from Planning with Diffusion for Flexible Behavior Synthesis. Guided sampling cod

KFAC-JAX - Second Order Optimization with Approximate Curvature in JAX Installation | Quickstart | Documentation | Examples | Citing KFAC-JAX KFAC-JAX

NEW RELEASE How Nebullvm Works • Tutorials • Benchmarks • Installation • Get Started • Optimization Examples Discord | Website | LinkedIn | Twitter Ne

LAV Learning from All Vehicles Dian Chen, Philipp Krähenbühl CVPR 2022 (also arXiV 2203.11934) This repo contains code for paper Learning from all veh

Intrusion-Detection-System-Using-CNN-and-Transfer-Learning This is the code for the paper entitled "A Transfer Learning and Optimized CNN Based Intrus

Description This repository contains code accompanying the following paper on the Make-It robotic flow chemistry platform developed by the Jensen Rese

Cooper About Cooper is a toolkit for Lagrangian-based constrained optimization in Pytorch. This library aims to encourage and facilitate the study of

30-Days-of-ML-Kaggle 🔥 About the Hands On Program 💻 Machine learning beginner → Kaggle competitor in 30 days. Non-coders welcome The program starts

Hugging Face Optimum 🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to t

OptiCL OptiCL is an end-to-end framework for mixed-integer optimization (MIO) with data-driven learned constraints. We address a problem setting in wh

sne4onnx A very simple tool for situations where optimization with onnx-simplifier would exceed the Protocol Buffers upper file size limit of 2GB, or

Athena Portfolio optimization is the process of selecting the best portfolio (asset distribution), out of the set of all portfolios being considered,

This is the official implementation of our paper: Bowen Wen, Wenzhao Lian, Kostas Bekris, and Stefan Schaal. "CaTGrasp: Learning Category-Level Task-R

EasyMCDM - Quick Installation methods Install with PyPI Once you have created your Python environment (Python 3.6+) you can simply type: pip3 install

Black-Box-Defense This repository contains the code and models necessary to replicate the results of our recent paper: How to Robustify Black-Box ML M

Black-Box-Defense This repository contains the code and models necessary to replicate the results of our recent paper: How to Robustify Black-Box ML M

autolfads-tf2 A TensorFlow 2.0 implementation of LFADS and AutoLFADS. Installati

B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search This is the offical implementation of the

OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.

AutoLGBM LightGBM + Optuna: no brainer auto train lightgbm directly from CSV files auto tune lightgbm using optuna auto serve best lightgbm model usin

Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe

JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c

Nonlinear Optimization Algorithms During my time as Scientific Assistant at the Karlsruhe Institute of Technology (Germany) I implemented various Opti

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

C++/ROS Source Codes for "Autonomous Driving on Curvy Roads without Reliance on Frenet Frame: A Cartesian-based Trajectory Planning Method" published in IEEE Trans. Intelligent Transportation Systems by Bai Li, Yakun Ouyang, Li Li, and Youmin Zhang.

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

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.

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

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

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

LINUX-AOS (Automatic Optimization System)

Internet-Ti.me Internet Time reference and (eventually) converter site, for planning things with your internet friends who aren't (yet) obsessed with

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.

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

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

CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces This is a repository for the following pape

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

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

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

Ruckig Instantaneous Motion Generation for Robots and Machines. Ruckig generates trajectories on-the-fly, allowing robots and machines to react instan

Clockwork Convnets for Video Semantic Segmentation This is the reference implementation of arxiv:1608.03609: Clockwork Convnets for Video Semantic Seg

Tools for mathematical optimization region

convnet-benchmarks Easy benchmarking of all public open-source implementations of convnets. A summary is provided in the section below. Machine: 6-cor

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.

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

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

Look into Palanteer and get an omniscient view of your program Palanteer is a set of lean and efficient tools to improve the quality of software, for

Qcover is an open source effort to help exploring combinatorial optimization problems in Noisy Intermediate-scale Quantum(NISQ) processor. It is devel

A computational optimization project towards the goal of gerrymandering the results of a hypothetical election in the UK.

PyGRANSO PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation Please check https://ncvx.org/PyGRANSO for detailed instructions (introd

LOOP: Learning Off-Policy with Online Planning Accepted in Conference of Robot Learning (CoRL) 2021. Harshit Sikchi, Wenxuan Zhou, David Held Paper In

SAPE Project page Paper Official implementation for the paper "SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization". Environment Cre

App-Blocker The text based version of my App Blocker that I planning on converting to GUI soon. Currently I am just uploading the appblocker.py file,

PEPit: Performance Estimation in Python This open source Python library provides a generic way to use PEP framework in Python. Performance estimation

Optimization-Planning-for-3D-ConvNets Code for the ICML 2021 paper: Optimization Planning for 3D ConvNets. Authors: Zhaofan Qiu, Ting Yao, Chong-Wah N

Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp

Computational Design and Dynamics of Soft Systems · This is a repository that contains the source code for generating the lecture notes, handouts, exe

End-To-End Optimization of LiDAR Beam Configuration arXiv | IEEE Xplore This repository is the official implementation of the paper: End-To-End Optimi

Aircraft design optimization made fast through modern automatic differentiation. Plug-and-play analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.

Designed a greedy algorithm based on Markov sequential decision-making process in MATLAB/Python to optimize using Gurobi solver, the wheel size, gear shifting sequence by modeling drivetrain constraints to achieve maximum laps in a race with a 2-hour time window.

PyPortfolioOpt has recently been published in the Journal of Open Source Software 🎉 PyPortfolioOpt is a library that implements portfolio optimizatio

GPOEO GPOEO is a micro-intrusive GPU online energy optimization framework for iterative applications. We also implement ODPP [1] as a comparison. [1]

{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”

{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”) is a new strategic transport modelling and data visualization framew

Medical Appointments No-shows Why do 20% of patients miss their scheduled appointments? A person makes a doctor appointment, receives all the instruct

Advisor Introduction Advisor is the hyper parameters tuning system for black box optimization. It is the open-source implementation of Google Vizier w

frePPLe Open source supply chain planning FrePPLe is an easy-to-use and easy-to-implement open source advanced planning and scheduling tool for manufa

deep_nn_model_with_only_python_100%_test_accuracy deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and differen

Machine Learning in Asset Management If you like this type of content then visit ML Quant site below: https://www.ml-quant.com/ Part One Follow this l

C3D C3D is a modified version of BVLC caffe to support 3D convolution and pooling. The main supporting features include: Training or fine-tuning 3D Co

Design-Bench Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box

Metacognitive Learning Tool box https://re.is.mpg.de What Is This? This repository contains two modules used to analyse metacognitive learning in huma

EMTAUC We provided a matlab implementation for an evolutionary multitasking AUC optimization framework (EMTAUC). In this code, SBGA is considered a ba

Safe Local Motion Planning with Self-Supervised Freespace Forecasting By Peiyun Hu, Aaron Huang, John Dolan, David Held, and Deva Ramanan Citing us Yo

Data-Scrapping SEO - the project uses various data scrapping and Google autocompletes API tools to provide relevant points of different keywords so that search engines can be optimized; as this information is gathered, the marketing team can target the top keywords to get your company’s website higher on a results page.

0. Introduction This repository contains the source code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning". Notes The netwo

OSMnx Examples OSMnx is a Python package to work with street networks and other spatial data from OpenStreetMap: retrieve, model, analyze, and visuali

AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

Overview This repository implements some common path planning algorithms used in robotics, including Search-based algorithms and Sampling-based algori

Optimizers Visualized Visualization of how different optimizers handle mathematical functions for optimization. Contents Installation Usage Functions

Scale complex AI/ML pipelines anywhere CodeFlare is a framework to simplify the integration, scaling and acceleration of complex multi-step analytics

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing

By wrapping the IBM Planning Analytics (TM1) REST API in a concise Python framework, TM1py facilitates Python developments for TM1. Interacting with T

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pycsminwel This is a locol minimization algorithm. Uses a quasi-Newton method with BFGS update of the estimated inverse hessian. It is robust against

MADGRAD Optimization Method A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization pip install madgrad Try it out! A best

redlight_approach redlight_approach is a Python package that computes an optimal motion plan during traffic light approach. RLA_demo.mov Given the par

Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a

Flyable - A python compiler for highly performant code Flyable is a Python compiler that generates efficient native code. It uses different techniques

Python HPC Optimizaciones incrementales de N-Body (all-pairs) con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámb