Xingjian Shi

HKO-7. Source code of paper "[NIPS2017] Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model"

automl_multimodal_benchmark. Repository for Multimodal AutoML Benchmark

aws-summit-2017-seoul. Demo codes in our presentation about MXNet in AWS Seoul Summit 2017

gluonnlp-gpt2. Python

CodeBERT. CodeBERT

mx-rcnn-1. Faster R-CNN, an MXNet implementation with distributed implementation and data parallelization.

pred-rnn. A TensorFlow implementation of our paper https://arxiv.org/abs/1804.06300.

mxnet. Efficient and Flexible Distributed Deep Learning Framework, for python, R, Julia and more

GluonNLP-Slot-Filling. Demonstrate how to use GluonNLP to perform intent detection and slot filling

autogluon-contrib-nlp. NLP Package that supports the AutoGluon Text functionality. Will be replaced by GluonNLP V 1.0 later. (https://github.com/dmlc/gluon-nlp)

benchmark_ops. Python

DCRNN. Implementation of Diffusion Convolutional Recurrent Neural Network

earth-forecasting-transformer. Python

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

deep_q_rl. Theano-based implementation of Deep Q-learning

release06_notebook_verification. Jupyter Notebook

transformers. 🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

gluon-nlp. NLP made easy

Associative_LSTM. LSTM with associative memory cells (http://arxiv.org/abs/1602.03032)

autogluon. AutoGluon: AutoML Toolkit for Deep Learning

titiler. A dynamic Web Map tile server

mnist-digits-as-stroke-sequences. Code project to transform the MNIST handwritten digit images to sequences of pen strokes to obtain a benchmark data set for sequence learning.

GraphSAGE. Representation learning on large graphs using stochastic graph convolutions.

DeBERTa. The implementation of DeBERTa

videogan. Generating Videos with Scene Dynamics. NIPS 2016.

EC2021_autogluon_notebook. Notebook that demonstrates AutoGluon (Notebook submission to EarthCube 2021)

dfn. Python

FewShotLearning. Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"

mshadow. Matrix Shadow:Lightweight CPU/GPU Matrix and Tensor Template Library in C++/CUDA for (Deep) Machine Learning