den-run-ai

DeepLearningExamples

Deep Learning Examples

asi-pytorch

Pytorch implementations of "Automatic Seismic Interpretation" publications and repositories

DCGAN-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deep-high-resolution-net.pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

DeepFlow

Pytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"

distdl

FanStore

faultSeg

Using synthetic datasets to train an end-to-end CNN for 3D fault segmentation (We are working on an improved version!)

GAN-Metrics

An empirical study on evaluation metrics of generative adversarial networks.

geo-style-keras

Keras implementation of neural style transfer applied to elastic subsurface models

guacamol

Benchmarks for generative chemistry

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

ios-demo-app

PyTorch iOS examples

livermask

LocoGAN

PyTorch implmentation of LocoGAN: https://arxiv.org/abs/2002.07897

MolBERT

mpi_learn

Distributed learning with mpi4py

ParticleGrid

Grid Generation

powerai

This repo contains ancillary information used to assist users of the PowerAI Frameworks. This repo will contain How To's, Readme's, Dockerfiles, etc. that can be consumed by users looking to get started using our various PowerAI features.

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

PyTorch-GAN

PyTorch implementations of Generative Adversarial Networks.

pytrax

Random walk to calculate the tortuosity tensor of images

rlax

sc19-dl-tutorial

Hands-on material for the SC19 tutorial, Deep Learning at Scale

torchbeast

A PyTorch Platform for Distributed RL

training

Reference implementations of training benchmarks

den-run-ai.io

blog website

evalplus

EvalPlus for rigourous evaluation of LLM-synthesized code

qchess

chess with q algo

textgrad

TextGrad: Automatic ''Differentiation'' via Text -- using large language models to backpropagate textual gradients.