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ad-papers

Papers on Computational Advertising

apq

[CVPR 2020] APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

artistic-videos

Torch implementation for the paper "Artistic style transfer for videos"

autoctr

code for https//research.fb.com/publications/towards-automated-neural-interaction-discovery-for-click-through-rate-prediction/

autofis

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

awesome-model-quantization

A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.

awesome-nas-papers

Awesome Neural Architecture Search Papers

ctr

CTR模型代码和学习笔记总结

deep-learning-21-examples

《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码

fast-neural-style

Feedforward style transfer

flownet2

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

flownet2-docker

Dockerfile and runscripts for FlowNet 2.0 (estimation of optical flow)

gomnist

GoMNIST is a Go driver for reading Yann LeCun's MNIST dataset of handwritten digits

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

once-for-all

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

recsys

计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

styletransfer

Real-time neural style transfer via meta networks

tensorflow

Computation using data flow graphs for scalable machine learning

tensorflow-vgg

VGG19 and VGG16 on Tensorflow

test_asr

videomoco

Official pytorch implementation of paper "VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples" (CVPR 2021).

videotransformer-pytorch

PyTorch implementation of a collections of scalable Video Transformer Benchmarks.

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch