Implement some metaheuristics and cost functions

Last update: Mar 23, 2022

Related tags

Deep Learning metaheuristics

Overview

Metaheuristics

This repot implement some metaheuristics and cost functions.

Metaheuristics

JAYA

Implement Jaya optimizer without constraints.

Cost functions

Himmelblau's function Himmelblau.png

References

[1]R. Venkata Rao, Jaya: An Advanced Optimization Algorithm and its Engineering Applications. Cham: Springer International Publishing, 2019. doi: 10.1007/978-3-319-78922-4.

[2]Wikipedia contributors, « Test functions for optimization », Wikipedia, The Free Encyclopedia., juin 27, 2021. https://en.wikipedia.org/w/index.php?title=Test_functions_for_optimization&oldid=1030693803 (consulté le oct. 01, 2021).

Owner

Adri1G

PhD student LS2N & Centrale Nantes. Interested in smart grids, embedded systems, electronics, Eurobot/ Coupe de Robotique and beautiful algorithms.

GitHub Repository

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Implement some metaheuristics and cost functions

Related tags

Overview

Metaheuristics

Metaheuristics

JAYA

Cost functions

References

Owner

Adri1G

This is the official code for the paper "Ad2Attack: Adaptive Adversarial Attack for Real-Time UAV Tracking".

Deep Networks with Recurrent Layer Aggregation

CLASP - Contrastive Language-Aminoacid Sequence Pretraining

Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation

Flybirds - BDD-driven natural language automated testing framework, present by Trip Flight

Autonomous Movement from Simultaneous Localization and Mapping

Conversion between units used in magnetism

Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition"

A supplementary code for Editable Neural Networks, an ICLR 2020 submission.

VOS: Learning What You Don’t Know by Virtual Outlier Synthesis

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

[EMNLP 2021] MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations

AI grand challenge 2020 Repo (Speech Recognition Track)

The official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach

Code for our NeurIPS 2021 paper Mining the Benefits of Two-stage and One-stage HOI Detection

Yolox-bytetrack-sample - Python sample of MOT (Multiple Object Tracking) using YOLOX and ByteTrack

git《Investigating Loss Functions for Extreme Super-Resolution》(CVPR 2020) GitHub:

Keras code and weights files for popular deep learning models.

The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.