pytodTOD: GPU-accelerated Outlier Detection via Tensor Operations
Stars: ✭ 131 (-13.82%)
dramaMain component extraction for outlier detection
Stars: ✭ 17 (-88.82%)
PyodA Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Stars: ✭ 5,083 (+3244.08%)
CCDCode for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]
Stars: ✭ 30 (-80.26%)
RemixautomlR package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.
Stars: ✭ 159 (+4.61%)
PysadStreaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)
Stars: ✭ 87 (-42.76%)
anomalibAn anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
Stars: ✭ 1,210 (+696.05%)
Isolation ForestA Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.
Stars: ✭ 139 (-8.55%)
SfmlearnerAn unsupervised learning framework for depth and ego-motion estimation from monocular videos
Stars: ✭ 1,661 (+992.76%)
ArflowThe official PyTorch implementation of the paper "Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation".
Stars: ✭ 134 (-11.84%)
Pytorch cppDeep Learning sample programs using PyTorch in C++
Stars: ✭ 114 (-25%)
CsiCSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)
Stars: ✭ 123 (-19.08%)
BcpdBayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available
Stars: ✭ 116 (-23.68%)
Flappy EsFlappy Bird AI using Evolution Strategies
Stars: ✭ 140 (-7.89%)
Repo 2019BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics
Stars: ✭ 133 (-12.5%)
GpndGenerative Probabilistic Novelty Detection with Adversarial Autoencoders
Stars: ✭ 112 (-26.32%)
PaysageUnsupervised learning and generative models in python/pytorch.
Stars: ✭ 109 (-28.29%)
Diff2vecReference implementation of Diffusion2Vec (Complenet 2018) built on Gensim and NetworkX.
Stars: ✭ 108 (-28.95%)
Unsupervised detectionAn Unsupervised Learning Framework for Moving Object Detection From Videos
Stars: ✭ 139 (-8.55%)
Log3cLog-based Impactful Problem Identification using Machine Learning [FSE'18]
Stars: ✭ 131 (-13.82%)
Back2future.pytorchUnsupervised Learning of Multi-Frame Optical Flow with Occlusions
Stars: ✭ 104 (-31.58%)
E3d lstme3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond
Stars: ✭ 129 (-15.13%)
Keras Oneclassanomalydetection[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.
Stars: ✭ 102 (-32.89%)
3dpose ganThe authors' implementation of Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations
Stars: ✭ 124 (-18.42%)
SplitbrainautoSplit-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. In CVPR, 2017.
Stars: ✭ 137 (-9.87%)
CleanlabThe standard package for machine learning with noisy labels, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.
Stars: ✭ 2,526 (+1561.84%)
PyoddsAn End-to-end Outlier Detection System
Stars: ✭ 141 (-7.24%)
CalcConvolutional Autoencoder for Loop Closure
Stars: ✭ 119 (-21.71%)
OneshottranslationPytorch implementation of "One-Shot Unsupervised Cross Domain Translation" NIPS 2018
Stars: ✭ 135 (-11.18%)
ForemastForemast adds application resiliency to Kubernetes by leveraging machine learnt patterns of application health to keep applications healthy and stable
Stars: ✭ 115 (-24.34%)
Lr Gan.pytorchPytorch code for our ICLR 2017 paper "Layered-Recursive GAN for image generation"
Stars: ✭ 145 (-4.61%)
Bio corexA flexible version of CorEx developed for bio-data challenges that handles missing data, continuous/discrete variables, multi-CPU, overlapping structure, and includes visualizations
Stars: ✭ 112 (-26.32%)
MocoUnofficial implementation with pytorch DistributedDataParallel for "MoCo: Momentum Contrast for Unsupervised Visual Representation Learning"
Stars: ✭ 112 (-26.32%)
Deepmappingcode/webpage for the DeepMapping project
Stars: ✭ 140 (-7.89%)
AndOfficial Pytorch Implementation for ICML'19 paper: Unsupervised Deep Learning by Neighbourhood Discovery
Stars: ✭ 133 (-12.5%)
Skip GanomalySource code for Skip-GANomaly paper
Stars: ✭ 107 (-29.61%)
DeepaiDetection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.
Stars: ✭ 104 (-31.58%)
Ml LibAn extensive machine learning library, made from scratch (Python).
Stars: ✭ 102 (-32.89%)
OpenubaA robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for Security Analytics. Developed with luv by Data Scientists & Security Analysts from the Cyber Security Industry. [PRE-ALPHA]
Stars: ✭ 127 (-16.45%)
DdflowDDFlow: Learning Optical Flow with Unlabeled Data Distillation
Stars: ✭ 101 (-33.55%)
VizukaExplore high-dimensional datasets and how your algo handles specific regions.
Stars: ✭ 100 (-34.21%)
StumpySTUMPY is a powerful and scalable Python library for modern time series analysis
Stars: ✭ 2,019 (+1228.29%)
Deepco3[CVPR19] DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency (Oral paper)
Stars: ✭ 127 (-16.45%)
Awesome Transfer LearningBest transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
Stars: ✭ 1,349 (+787.5%)
Text SummarizerPython Framework for Extractive Text Summarization
Stars: ✭ 96 (-36.84%)
Self Supervised Relational ReasoningOfficial PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Stars: ✭ 89 (-41.45%)
TybaltTraining and evaluating a variational autoencoder for pan-cancer gene expression data
Stars: ✭ 126 (-17.11%)