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5421project1

HKUST 5421 Project1

adaptivefourierneuraloperator

albert

allennlp

An open-source NLP research library, built on PyTorch.

amazon-dsstne

Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models

amazon-s3-plugin-for-pytorch

anonymoussubmission_automl

Code of Submission "Multimodal AutoML on Structured Tables with Text Fields"

apls

Python code to evaluate the APLS metric

apps

Automated Programming Progress Standard (APPS)

arcade-learning-environment

The Arcade Learning Environment (ALE) -- a platform for AI research.

arctic-captions

associative_lstm

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

async_deep_reinforce

Asynchronous Methods for Deep Reinforcement Learning

atari

Persistent advantage learning dueling double DQN for the Arcade Learning Environment.

autocfg

All you need is a config for automl

autogluon

AutoGluon: AutoML Toolkit for Deep Learning

autogluon-benchmarking

Benchmarking Utilities for AutoGluon

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)

autograd

Efficiently computes derivatives of numpy code.

automl_multimodal_benchmark

Repository for Multimodal AutoML Benchmark

aws-batch-config

aws-efa-eks

Deploying P4d in EKS utilizing GPUDirectRDMA over EFA

aws-efa-nccl-baseami-pipeline

EFA/NCCL base AMI build Packer and CodeBuild/Pipeline files. Also base Docker build files to enable EFA/NCCL in containers

aws-orbit-workbench-1

Tying up all components around to deliver a solid and integrated data environment powered by AWS services.

aws-summit-2017-seoul

Demo codes in our presentation about MXNet in AWS Seoul Summit 2017

benchmark_ops

bigcode-evaluation-harness

A framework for the evaluation of autoregressive code generation language models.

blanc

Human-free quality estimation of document summaries

blocksparse

Efficient GPU kernels for block-sparse matrix multiplication and convolution

boon

Code for results presented in the BOON paper