Popular GitHub Repositories for Symmetric Multiprocessing

The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"

(CVPR'20 Oral) Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild

Distributed Computing for AI Made Simple

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

[High Performance / MAX 30 FPS] RaspberryPi3(RaspberryPi/Raspbian Stretch) or Ubuntu + Multi Neural Compute Stick(NCS/NCS2) + RealSense D435(or USB Camera or PiCamera) + MobileNet-SSD(MobileNetSSD) + Background Multi-transparent(Simple multi-class segmentation) + FaceDetection + MultiGraph + MultiProcessing + MultiClustering

Orkhon: ML Inference Framework and Server Runtime

DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN

Анализ трафика на круговом движении с использованием компьютерного зрения

Attention Kernels for Symmetric Power Transformers

Regression Graph Neural Network (regGNN) for cognitive score prediction.

? Modularised Evolutionary Algorithms For Python with Optional JIT and Multiprocessing (Ray) support. Inspired by PyTorch Lightning

Reinforcement Learning for Super Mario Bros using A3C on GPU

Automatic GPU, TPU, FPGA, Xeon Phi, Multithreaded, Distributed, etc. offloading for scientific machine learning (SciML) and differential equations

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining, ICML'23

multiprocess unsupervised chinese_detect_words ngram_combination

[arXiv'21] Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning

Multi agent gym environment based on the classic Snake game with implementations of various reinforcement learning algorithms in pytorch

An Explainable Geometric-Weighted Graph Attention Network (xGW-GAT) for Identifying Functional Networks Associated with Gait Impairment

Real-time sentiment analysis on tweets using tweepy and kafka. Graphed using the output of a neural network and Dash/Plotly.