Taichi TAKAYAMA's starred repositories
torcharrow
High performance model preprocessing library on PyTorch
Dassl.pytorch
A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.
EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Smoothly-Blend-Image-Patches
Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.
SRGAN_PytorchLightning
My implementation of article Super Resolution GAN using Pytorch Lightning
Satellite-image-SRGAN
Using GAN to do super resolution of satellite images
MSRN-PyTorch
This repository is a PyTorch version of the paper "Multi-scale Residual Network for Image Super-Resolution" (ECCV 2018).
super-resolution
Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
sr-pytorch-lightning
Super-Resolution with pytorch-lightning
techniques
Techniques for deep learning with satellite & aerial imagery
mlflow-prefect-jupyter-docker-compose
MLflow and Prefect with docker-compose
superbenchmark
A validation and profiling tool for AI infrastructure
pytorch-enhance
Open-source Library of Image Super-Resolution Models, Datasets, and Metrics for Benchmarking or Pretrained Use
docker-compose-healthchecks
Collection of Docker Compose healthcheck examples. Tested with Docker Compose version 3.8
docker-compose-healthcheck
How to wait for container X before starting Y using docker-compose healthcheck
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
semi-supervised-pytorch
Implementations of various VAE-based semi-supervised and generative models in PyTorch