alexteua

alexteua's Stars

• karpathy/minGPT

  A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

  Language:Python20.3k257722.5k

• NVlabs/stylegan2

  StyleGAN2 - Official TensorFlow Implementation

  Language:Python11k37102.5k

• Farama-Foundation/Gymnasium

  An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

  Language:Python7.5k42473840

• NVlabs/stylegan3

  Official PyTorch implementation of StyleGAN3

  Language:Python6.5k552561.1k

• idealo/image-super-resolution

  🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

  Language:Python4.7k102216769

• podgorskiy/ALAE

  [CVPR2020] Adversarial Latent Autoencoders

  Language:Python3.5k8469558

• eladrich/pixel2style2pixel

  Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework

  Language:Jupyter Notebook3.2k62318568

• NVlabs/MUNIT

  Multimodal Unsupervised Image-to-Image Translation

  Language:Python2.7k75105483

• wenbihan/reproducible-image-denoising-state-of-the-art

  Collection of popular and reproducible image denoising works.

  2.4k11710508

• mingyuliutw/UNIT

  Unsupervised Image-to-Image Translation

  Language:Python2k59110363

• junyanz/BicycleGAN

  Toward Multimodal Image-to-Image Translation

  Language:Python1.5k4894254

• NVlabs/noise2noise

  Noise2Noise: Learning Image Restoration without Clean Data - Official TensorFlow implementation of the ICML 2018 paper

  Language:Python1.4k430310

• mmorise/World

  A high-quality speech analysis, manipulation and synthesis system

  Language:C++1.2k7092255

• yu4u/noise2noise

  An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data"

  Language:Python1.1k4550237

• pix2pixzero/pix2pix-zero

  Zero-shot Image-to-Image Translation [SIGGRAPH 2023]

  Language:Python1.1k343179

• tatuylonen/wiktextract

  Wiktionary dump file parser and multilingual data extractor

  Language:Python8251630287

• gemengtju/Tutorial_Separation

  This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.

  Language:MATLAB44921295

• juglab/n2v

  This is the implementation of Noise2Void training.

  Language:Python40920102112

• jcvasquezc/DisVoice

  feature extraction from speech signals

  Language:Jupyter Notebook355132980

• NVlabs/selfsupervised-denoising

  High-Quality Self-Supervised Deep Image Denoising - Official TensorFlow implementation of the NeurIPS 2019 paper

  Language:Python30622038

• czbiohub/noise2self

  A framework for blind denoising with self-supervision.

  Language:Jupyter Notebook291161067

• LS4GAN/uvcgan

  Code accompanying UVCGAN paper

  Language:Python134102222

• JSubelj/g910-gkey-macro-support

  GKey support for Logitech G910 Keyboard on Linux

  Language:Python99115831

• Yochengliu/MLIC-KD-WSD

  Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection (ACM MM 2018)

  Language:C++5851324

• A2Amir/Pix2Pix-for-Semantic-Segmentation-of-Satellite-Images

  The presented experiment aims at using Pix2Pix network to segment the building footprint from Satellite Images.

  Language:Jupyter Notebook523318

• sudipansaha/dcvaVHROptical

  Deep Change Vector Analysis

  Language:Python52359

• ldong1111/GraphemeBERT

  This is the source code of the paper "Neural grapheme-to-phoneme conversion with pretrained grapheme models

  Language:Python45717

• Fraunhofer-SCAI/wavelet_pooling

  Adaptive wavelet pooling for CNN in PyTorch, AISTATS 2021.

  Language:Python32302

• gambolputty/wiktionary-de-parser

  Extract data from German Wiktionary XML files.

  Language:Jupyter Notebook24358

• aws-solutions-library-samples/guidance-for-geospatial-insights-for-sustainability-on-aws

  This Guidance helps customers observe land use changes using geospatial data to support supply chain best practices. Customers can monitor changes in forest density using an Amazon SageMaker geospatial capability that simplifies the process of analyzing satellite images for changes in vegetation.

  Language:Jupyter Notebook14515