Maschinelles Lernen · GitHub

Euclidean Neural Networks

Training and evaluating state-of-the-art deep learning CNN architectures for plant disease classification task.

Set up CUDA for machine learning (and gaming) on macOS using a NVIDIA eGPU

A tutorial on TensorFlow

MINE: Mutual Information Neural Estimation in pytorch (unofficial)

TensorFlow2.0 官方教程翻译，基本概念讲解、实战项目、TensorFlow2.0编程技巧。

This repository collates a number of MATLAB examples demonstrating Scientific Machine Learning (SciML) and Physics Informed Machine Learning.

Deep Learning Transformer models in MATLAB

Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.

pytorch implementation of the different DeepGaze models

This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as described in "A General Framework for Uncertainty Estimation in Deep Learning" (Loquercio, Segù, Scaramuzza. RA-L 2020).

Deep generative models of voxel grids for structure-based drug discovery

👨‍🔬 In Russian: Обновляемая структурированная подборка бесплатных ресурсов по тематикам Data Science: курсы, книги, открытые данные, блоги и готовые решения.

Official code for Cotatron @ INTERSPEECH 2020

[W-NUT'20] Punctuation Restoration using Transformer Models for High-and Low-Resource Languages

OCR, Archive, Index and Search: Implementation agnostic OCR framework.

All lecture notes, slides and assignments from CS224n: Natural Language Processing with Deep Learning class by Stanford

Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"

Learning and Building Convolutional Neural Networks using PyTorch

A tool for efficient semi-supervised video object segmentation (great results with minimal manual labor) and a dataset for benchmarking

[ICCV 2023] MeMOTR: Long-Term Memory-Augmented Transformer for Multi-Object Tracking

a repo sharing Bayesian Neural Network recent papers

Auto-Annotate - Automatically annotate your entire image directory by a single command. As simple as saying - "Annotate all the street sign (label) in the autonomous car dataset (directory)" and BAM! DONE. Each and every image with a street sign in the diverse dataset directory containing images of all sorts which have a street sign are filtered and the segmentation annotation is performed in a single command. The Auto-Annotate tool provides auto annotation of segmentation masks for the objects in the images inside some directory based on the labels. Auto-Annotate is able to provide automated annotations for the labels defined in the COCO Dataset and also supports Custom Labels.

Feature Books for Machine Learning