SCL📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).
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ganbertEnhancing the BERT training with Semi-supervised Generative Adversarial Networks
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LibFewShotLibFewShot: A Comprehensive Library for Few-shot Learning.
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deviation-networkSource code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection
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subwAIScripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classification
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SimMIMThis is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".
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DeFMO[CVPR 2021] DeFMO: Deblurring and Shape Recovery of Fast Moving Objects
Stars: ✭ 144 (+193.88%)
HiCECode for ACL'19 "Few-Shot Representation Learning for Out-Of-Vocabulary Words"
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multilingual kwsFew-shot Keyword Spotting in Any Language and Multilingual Spoken Word Corpus
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rankpruning🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.
Stars: ✭ 81 (+65.31%)
aitlasAiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.
Stars: ✭ 134 (+173.47%)
Image-ClassificationPre-trained VGG-Net Model for image classification using tensorflow
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VoskVOSK Speech Recognition Toolkit
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head-network-distillation[IEEE Access] "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems" and [ACM MobiCom HotEdgeVideo 2019] "Distilled Split Deep Neural Networks for Edge-assisted Real-time Systems"
Stars: ✭ 27 (-44.9%)
KerasUIUI for Keras to implement image classification written in python and django
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Cct[CVPR 2020] Semi-Supervised Semantic Segmentation with Cross-Consistency Training.
Stars: ✭ 171 (+248.98%)
pytorch-cifar-model-zooImplementation of Conv-based and Vit-based networks designed for CIFAR.
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Stylealign[ICCV 2019]Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Transition
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MixNet-PyTorchConcise, Modular, Human-friendly PyTorch implementation of MixNet with Pre-trained Weights.
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Skin Lesions Classification DCNNsTransfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification
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pywslPython codes for weakly-supervised learning
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attMPTI[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation
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PyramidnetPytorch implementation of pyramidnet
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mybabeMyBB CAPTCHA Solver using Convolutional Neural Network in Keras
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Good PapersI try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
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jpetstore-kubernetesModernize and Extend: JPetStore on IBM Cloud Kubernetes Service
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Improvedgan PytorchSemi-supervised GAN in "Improved Techniques for Training GANs"
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P-tuningA novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
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Triple GanSee Triple-GAN-V2 in PyTorch: https://github.com/taufikxu/Triple-GAN
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imannotateImage annotation tool to make Machine Learning or others stuffs
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shake-drop pytorchPyTorch implementation of shake-drop regularization
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UniFormer[ICLR2022] official implementation of UniFormer
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few-shot-segmentationPyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans
Stars: ✭ 78 (+59.18%)
Accel Brain CodeThe purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.
Stars: ✭ 166 (+238.78%)
Deep Sad PytorchA PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
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Pro-GNNImplementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
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UdaUnsupervised Data Augmentation (UDA)
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FUSIONPyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"
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