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Code for Arxiv Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle
Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
Awesome-LLM: a curated list of Large Language Model
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
This is an unofficial implementation of the paper “PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization”.
A tutorial on object detection using TensorFlow
This is the official repository to the WACV 2021 paper "Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows" by Marco Rudolph, Bastian Wandt and Bodo Rosenhahn.
Language Understanding Evaluation benchmark for Chinese: datasets, baselines, pre-trained models,corpus and leaderboard
A curated list of awesome anomaly detection resources
A reference system for end to end live streaming video. Capture, encode, package, uplink, origin, CDN, and player.
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explana…
The Tensorflow implementation of some models like ResNet and WideResNet on the Cifar-10 or Cifar-100 dataset.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks
Multimodal Unsupervised Image-to-Image Translation
A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.
Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Graph Neural Network Library for PyTorch
Code for the NeurIPS'17 paper "DropoutNet: Addressing Cold Start in Recommender Systems"
A TensorFlow recommendation algorithm and framework in Python.
Pytorch implementation of convolutional neural network visualization techniques
Bootstrap Kubernetes the hard way. No scripts.