poolio

poolio's Stars

• pytorch/pytorch

  Tensors and Dynamic neural networks in Python with strong GPU acceleration

  Language:Python85.3k1.7k47.8k23k

• jax-ml/jax

  Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

  Language:Python30.9k3365.8k2.8k

• facebookresearch/Detectron

  FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

  Language:Python26.3k9409265.5k

• mxgmn/WaveFunctionCollapse

  Bitmap & tilemap generation from a single example with the help of ideas from quantum mechanics

  Language:C#23.5k501521.3k

• alexjc/neural-enhance

  Super Resolution for images using deep learning.

  Language:Python11.9k39801.4k

• dunovank/jupyter-themes

  Custom Jupyter Notebook Themes

  Language:CSS9.8k1563991.1k

• ashawkey/stable-dreamfusion

  Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion.

  Language:Python8.4k129301736

• pytorch/tutorials

  PyTorch tutorials.

  Language:Jupyter Notebook8.3k1798254.1k

• transcranial/keras-js

  Run Keras models in the browser, with GPU support using WebGL

  Language:JavaScript5k179115502

• cysmith/neural-style-tf

  TensorFlow (Python API) implementation of Neural Style

  Language:Python3.1k129106825

• igul222/improved_wgan_training

  Code for reproducing experiments in "Improved Training of Wasserstein GANs"

  Language:Python2.4k8092671

• thu-ml/zhusuan

  A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow

  Language:Python2.2k14461418

• tdeboissiere/DeepLearningImplementations

  Implementation of recent Deep Learning papers

  Language:Python1.8k13274649

• google-research/disentanglement_lib

  disentanglement_lib is an open-source library for research on learning disentangled representations.

  Language:Python1.4k3427203

• HyperGAN/HyperGAN

  Composable GAN framework with api and user interface

  Language:Python1.2k41113164

• dmlc/minpy

  NumPy interface with mixed backend execution

  Language:Python1.1k6296110

• NVlabs/NVAE

  The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper)

  Language:Python1k1846164

• LMescheder/GAN_stability

  Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

  Language:Jupyter Notebook9182219114

• leegao/readme2tex

  Renders TeXy Math for Github Readmes

  Language:Python9052137194

• dyelax/Adversarial_Video_Generation

  A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

  Language:Python7363435184

• google-deepmind/dsprites-dataset

  Dataset to assess the disentanglement properties of unsupervised learning methods

  Language:Jupyter Notebook48715669

• loshchil/AdamW-and-SGDW

  Decoupled Weight Decay Regularization (ICLR 2019)

  Language:Lua2677328

• hiwonjoon/tf-vqvae

  Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

  Language:Jupyter Notebook2598341

• ravidziv/IDNNs

  explore DNNs via Infomration

  Language:Python259191491

• miyosuda/disentangled_vae

  Replicating "Understanding disentangling in β-VAE"

  Language:Python1958738

• renmengye/tensorflow-forward-ad

  Forward-mode Automatic Differentiation for TensorFlow

  Language:Python14011518

• fzenke/pub2018superspike

  Code from our paper: SuperSpike: Supervised learning in multi-layer spiking neural networks.

  Language:C++565111

• maithraraghu/MLcites

  This repository contains citation data for papers published in NeurIPS in 2014 - 2018, and ICML 2017, 2018. It also contains the code to collect this data.

  Language:Jupyter Notebook24417

• zihangdai/cegan_iclr2017

  Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"

  Language:Python23405

• fzenke/ssbm

  A curated list of spiking network supervised learning benchmarks

  Language:Python7401