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idinvert_pytorch

[ECCV 2020] In-Domain GAN Inversion for Real Image Editing (PyTorch code)

igm

Progressive Colorization via Iterative Generative Models

ilvr_adm

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (ICCV 2021 Oral)

image-classification-pytorch

Intro to PyTorch | Build an Image Classification Model using Convolutional Neural Networks in PyTorch

image-spatial-index-complexity-calculation

This code can be used to calculate Spatial Index (Complexity Measure) of an image or dataset. This can be helpful in identifying how complex a scene or a particular image is.

image-super-resolution-via-iterative-refinement

Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch

image2ddim

Image starting noise reconstruction for Denoising Diffusion Implicit Models(DDIMs)

imagen-pytorch

Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch

img_classification_benchmark

A performance benchmark of recent image classification models in deep learning

improved-diffusion

Release for Improved Denoising Diffusion Probabilistic Models

inf-vae

Inf-VAE: A Variational Autoencoder Framework to Integrate Homophily and Influence in Diffusion Prediction

infusion

This repository contains the code for the paper: "Learning to Generate Samples from Noise through Infusion Training.", Florian Bordes, Sina Honari, Pascal Vincent. https://arxiv.org/abs/1703.06975

init-pools-dal

This is the official code implementation of our paper, On Initial Pools for Deep Active Learning, accepted at the Pre-registration Workshop at NeurIPS 2020.

inpaint-gan

An idea for inpainting with unconditional GANs

intro_dgm

An Introduction to Deep Generative Modeling: Examples

itest

itoken

java-library_management_system

Java application for managing books borrowing in libraries. Using Swing GUI framework , JDBC database connector for MySQL database

jax-variational-diffwave

Jax/Flax implementation of Variational-DiffWave.

jdm

Learning Joint Probability Distribution via Diffusion Probabilistic Models

joint-vae

Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2:

k-diffusion

Karras et al. (2022) diffusion models for PyTorch

k-means-clustering

Implement k-means clustering on CIFAR10 dataset

kalman

MATLAB experiments with Kalman filters (regular & unscented)

kalman-filter

Very simple discrete kalman filtering

kalman-filter-object-tracking

2D Object Tracking Using Kalman filter

keda

KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes

kernel-prior-diffusion

kmeans_pytorch

kmeans using PyTorch

kmeans_pytorch-1

pytorch implementation of basic kmeans algorithm(lloyd method with forgy initialization) with gpu support