Popular GitHub Repositories for Maximum Mean Discrepancy

MiniMax-01 is a simple implementation of the MiniMax algorithm, a widely used strategy for decision-making in two-player turn-based games like Tic-Tac-Toe. The algorithm aims to minimize the maximum possible loss for the player, making it a popular choice for developing AI opponents in various game scenarios.

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

Native, Apple Silicon–only local LLM server. Similar to Ollama, but built on Apple's MLX for maximum performance on M‑series chips. SwiftUI app + SwiftNIO server with OpenAI‑compatible endpoints.

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_

Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

[ICLR 2025] Official implementation of Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration

Connect your AI app directly to your data with a full stack solution. Fully connected Agentic Graph RAG pipelines mean you can focus on fine tuning your app and not building data infrastructure.

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

Python library for YOLO small object detection and instance segmentation

Easy whole-brain modeling for computational neuroscientists ??????

PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

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A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.

Learning kernels to maximize the power of MMD tests

目标检测 - R-CNN算法实现

OmniCoreAgent is the complete AI development platform that combines two powerful systems into one revolutionary ecosystem. Build production-ready AI agents with OmniAgent, use the advanced MCP client with MCPOmni Connect, or combine both for maximum power.

A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.