luuyin

SupContrast

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

prototypical-networks

Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

Prototypical-Networks-for-Few-shot-Learning-PyTorch

Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch

deep-active-learning

Deep Active Learning

ImageNet_Utils

:arrow_double_down: Utils to help download images by id, crop bounding box, label images, etc.

few-shot-ssl-public

Meta Learning for Semi-Supervised Few-Shot Classification

sparse_learning

Sparse learning library and sparse momentum resources.

prototypical-network-pytorch

A re-implementation of "Prototypical Networks for Few-shot Learning"

bag-of-words

Python Implementation of Bag of Words for Image Recognition using OpenCV and sklearn

Synaptic-Flow

dd-ml-segmentation-benchmark

DroneDeploy Machine Learning Segmentation Benchmark

prototypical-networks-tensorflow

Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

Bag-of-Visual-Words-Python

Implementing Bag of Visual words approach for object classification and detection

snip

Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.

GraSP

Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH

gnn_few_shot_cifar100

This is the PyTorch-0.4.0 implementation of few-shot learning on CIFAR-100 with graph neural networks (GNN)

G-SimCLR

This is the code base for paper "G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling" by Souradip Chakraborty, Aritra Roy Gosthipaty and Sayak Paul.

tiered-imagenet-tools

Tools for generating tieredImageNet dataset and processing batches

active_learning

In-Time-Over-Parameterization

[ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy

cifar100coarse

Build PyTorch CIFAR100 using coarse labels

novelty-detection

Analyzing basic network responses to novel classes

FreeTickets

[ICLR 2022] "Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity" by Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

align-hier

An implementation of our CVPR 2016 work 'Scale-Aware Alignment of Hierarchical Image Segmentation'

ACDC

Code for reproducing "AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks" (NeurIPS 2021)

image-segmentation-kmeans

Basic image segmentation & compression using K-Means clustering

Synflow_SNIP_GraSP

Comparison of method "Pruning at initialization prior to training" (Synflow/SNIP/GraSP) in PyTorch

PbLite-Contour-Detection

A simplified implementation of contour detection from the paper https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/papers/amfm_pami2010.pdf

dynamic-pruning

Knowledge-Elicitation-using-Deep-Metric-Learning-and-Psychometric-Testing

Codes for "Knowledge Elicitation using Deep Metric Learning and Psychometric Testing" (ECML 2020)