Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking, Post Ranking, Relevance, LLM and RL. Please cite our p…

This is the official PyTorch implementation for the paper: "EulerNet: Adaptive Feature Interaction Learning via Euler’s Formula for CTR Prediction".

Bayesian Deep Learning Benchmarks

Code for paper "Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning"

Codes for TPM, a tree based model for watch time prediction

I release the code for fine-tuning GLM on released GPT4 data. This repo is just for sharing and fun.

predicting expression effects of human genome variants ab initio from sequence

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

MB-STR SIGIR22

【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容

Fast, integrative fine mapping with functional data

Source code for paper "MolSHAP: Interpreting Structure-Activity Relationships for Compound Optimization"

Single-cell disease relevance score (scDRS)

Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks

Streamlit — A faster way to build and share data apps.

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

Learning Sparse Neural Networks through L0 regularization

codes for KPGT (Knowledge-guided Pre-training of Graph Transformer)

SCAVENGE is a method to optimize the inference of functional and genetic associations to specific cells at single-cell resolution.

Scissor package

Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets

Implementation of Gibbs sampling for spike and slab priors