Make your master artistic punk avatar through machine learning world famous paintings.
Overview
Owner
Philipjhc
Efficient training of deep recommenders on cloud.
HybridBackend Introduction HybridBackend is a training framework for deep recommenders which bridges the gap between evolving cloud infrastructure and
Image restoration with neural networks but without learning.
Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s
Official PyTorch implementation of Joint Object Detection and Multi-Object Tracking with Graph Neural Networks
This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.
Mercury: easily convert Python notebook to web app and share with others
Mercury Share your Python notebooks with others Easily convert your Python notebooks into interactive web apps by adding parameters in YAML. Simply ad
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations
[SIGMETRICS 2022] One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search paper | website One Proxy Device Is Enough for Hardware-Aware Neural Architec
Using machine learning to predict undergrad college admissions.
College-Prediction Project- Overview: Many have tried, many have failed. Few trailblazers are ambitious enought to chase acceptance into the top 15 un
Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
Core ML Tools Use coremltools to convert machine learning models from third-party libraries to the Core ML format. The Python package contains the sup
MIRACLE (Missing data Imputation Refinement And Causal LEarning)
MIRACLE (Missing data Imputation Refinement And Causal LEarning) Code Author: Trent Kyono This repository contains the code used for the "MIRACLE: Cau
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2020 Links Doc
deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and different optimization choices
deep_nn_model_with_only_python_100%_test_accuracy deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and differen
Official PyTorch implementation of "VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization" (CVPR 2021)
VITON-HD — Official PyTorch Implementation VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization Seunghwan Choi*1, Sunghyun Pa
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re
Official repository of DeMFI (arXiv.)
DeMFI This is the official repository of DeMFI (Deep Joint Deblurring and Multi-Frame Interpolation). [ArXiv_ver.] Coming Soon. Reference Jihyong Oh a
Latex code for making neural networks diagrams
PlotNeuralNet Latex code for drawing neural networks for reports and presentation. Have a look into examples to see how they are made. Additionally, l
MDMM - Learning multi-domain multi-modality I2I translation
Multi-Domain Multi-Modality I2I translation Pytorch implementation of multi-modality I2I translation for multi-domains. The project is an extension to
This repository contains pre-trained models and some evaluation code for our paper Towards Unsupervised Dense Information Retrieval with Contrastive Learning
Contriever: Towards Unsupervised Dense Information Retrieval with Contrastive Learning This repository contains pre-trained models and some evaluation
CvT2DistilGPT2 is an encoder-to-decoder model that was developed for chest X-ray report generation.
CvT2DistilGPT2 Improving Chest X-Ray Report Generation by Leveraging Warm-Starting This repository houses the implementation of CvT2DistilGPT2 from [1
Self-Supervised depth kalilia
Self-Supervised depth kalilia
As a part of the HAKE project, includes the reproduced SOTA models and the corresponding HAKE-enhanced versions (CVPR2020).
HAKE-Action HAKE-Action (TensorFlow) is a project to open the SOTA action understanding studies based on our Human Activity Knowledge Engine. It inclu



