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Type: Organization
Type: Organization
Attention-based Dropout Layer for Weakly Supervised Object Localization, CVPR 2019 (Oral)
Code base for our paper " Adversarial Scene Editing: Automatic Object Removal from Weak Supervision" appearing in NIPS 2018.
Attention Guided Graph Convolutional Networks for Relation Extraction (authors' PyTorch implementation for the ACL19 paper)
Bringing node2vec and word2vec together for cool stuff
S.M.Ali Eslam et.al. Attend, Infer, Repeat: Fast Scene Understanding with Generative Models ICML16
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
Original implementation of Spatially Invariant Attend, Infer, Repeat (SPAIR) in TensorFlow.
:page_facing_up: 适合中文的简历模板收集(LaTeX,HTML/JS and so on)由 @hoochanlon 维护
⚡️ 百度网盘不限速下载器 BND,支持 Windows、Mac 和 Linux。
A Pytorch Implementation of the Beta-VAE
Class Activation Mapping
Adversarial Autoencoders with Constant-Curvature Latent Manifolds (2018, https://arxiv.org/abs/1812.04314)
Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.
Sample code for Constrained Graph Variational Autoencoders
This is a pytorch implementation of Deep-INFOMAX.
Structured Prediction with Deep Value Networks (PyTorch implementation)
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?" ICCV2019 Oral https://www.deepgcns.org
Pytorch Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?" ICCV2019 Oral https://www.deepgcns.org
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
This is a pytorch re-implementation of Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition
Experiments for understanding disentanglement in VAE latent representations
PyTorch implementation of the NIPS 2017 paper - Unsupervised Learning of Disentangled Representations from Video
Example code for the paper "Understanding deep learning requires rethinking generalization"
G-SchNet - a generative model for 3d molecular structures
Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.
Graph Convolution Network for PyTorch
Pytorch implementations of generative models: AIR, DRAW, InfoGAN, DCGAN, SSVAE
Gaussian mixture models in PyTorch.
Supervised community detection with line graph neural networks
GrabNet: A Generative model to generate realistic 3D hands grasping unseen objects (ECCV2020)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.