基于Pytorch和torchtext的自然语言处理深度学习框架。
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Updated
Dec 14, 2020 - Python
基于Pytorch和torchtext的自然语言处理深度学习框架。
🎯 Task-oriented embedding tuning for BERT, CLIP, etc.
Extremely simple and fast word2vec implementation with Negative Sampling + Sub-sampling
Reinforced Negative Sampling over Knowledge Graph for Recommendation, WWW2020
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021
This repository collects 100 papers related to negative sampling methods.
Implements various negative sampling techniques for learning knowledge graph embeddings
SimXNS is a research project for information retrieval. This repo contains official implementations by MSRA NLC team.
This Machine Learning project deals with Coupon Recommendations based on Revenue Uplift
⚡️ Implementation of TRON: Transformer Recommender using Optimized Negative-sampling, accepted at ACM RecSys 2023.
A PyTorch Implementation of the Skipgram Negative Sampling Word2Vec Model as Described in Mikolov et al.
Embedding模型代码和学习笔记总结
[Paper][IJCNN2023] Modality-Aware Negative Sampling for Multi-modal Knowledge Graph Embedding
Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction
PyTorch implementation for " Conditional Negative Sampling for Contrastive Learning of Visual Representations" (https://arxiv.org/abs/2010.02037).
Some demo word2vec models implemented with pytorch, including Continuous-Bag-Of-Words / Skip-Gram with Hierarchical-Softmax / Negative-Sampling.
Maximizing Revenue with Individualized Coupon Optimization Using Tree-Based Models
CBOW, Skip-gram with nagative sampling - Pytorch
gdp is generating distributed representation code sets written by pytorch. This code sets is including skip gram and cbow.
SkipGram NegativeSampling implemented in PyTorch.
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