Maschinelles Lernen · GitHub

Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness" (ICLR 2019 Oral)

Open datasets for training and benchmarking AI and robotic systems in agriculture and off-road environments

List of resources for mineral exploration and machine learning, generally with useful code and examples.

• These you can reproduce the output geospatially from the data given.

Pytorch implementation of ResUnet and ResUnet ++

DeepLabv3+ built in TensorFlow

AMD's graph optimization engine.

FlyDSL is the Python front‑end of the project: a Flexible Layout Python DSL for expressing tiling, partitioning, data movement, and kernel structure at a high level.

A fully functional and simple Machine Learning library made entirely from scratch with Python.

⚡ In-Memory Vector Search Engine & HNSW ANN Graph in Java 21 Loom. Sub-millisecond KNN retrieval, 8-bit scalar quantization (SQ8), 16,000+ QPS.

Babel Street Analytics Client Library for Python

Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) in PyTorch

PyTorch implementation of Glow

A collection of stand-alone Python machine learning recipes

Introduction to Deep Learning for Natural Language Processing

Code for Neural Motifs: Scene Graph Parsing with Global Context (CVPR 2018)

基于Pytorch的Bert应用，包括命名实体识别、情感分析、文本分类以及文本相似度等

[TPAMI 2024 & CVPR 2023] PyTorch code for DGM4: Detecting and Grounding Multi-Modal Media Manipulation and beyond

Scripts to help you set up your Ubuntu quickly, especially if you're in any subfield of Data Science or AI!