Graph Attention Networks (https://arxiv.org/abs/1710.10903)

This repository contains a custom implementation of the BERT model, fine-tuned for specific tasks, along with an implementation of Low Rank Approximation (LoRA). The models are optimized for high p…

PnPXAI Framework: Simplifying AI Model Explanations with Algorithm Recommendation and Automatic Optimization

[SIGIR'2023] "DCCF: Disentangled Contrastive Collaborative Filtering"

A curated model zoo for recommendation tasks

Diffusion Recommender Model

This repository provides details and links to the ACL anthology corpus/collection including .bib, .pdf and grobid extractions of the pdfs

An open-source framework for self-supervised recommender systems.

KGCN pytorch model implementation

A k-means variation that produces clusters of the same size utilizing the scikit-learn API and related utilities

A context aware recommender system using a user-based collaborative approach

[ECIR'24] Implementation of "Large Language Models are Zero-Shot Rankers for Recommender Systems"

[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"

Acceptance rates for the major AI conferences

(RecSys 2020) Adaptively Distilled Exemplar Replay towards Continual Learning for Session-based Recommendation [Best Short Paper]

CIFAR10, CIFAR100 results with VGG16,Resnet50,WideResnet using pytorch-lightning

Graph Trend Filtering Networks for Recommendations, SIGIR'2022

PyTorch Implementation for Neural Graph Collaborative Filtering

Graph Neural Networks for Social Recommendation, WWW'19

[WWW'2023] "DCRec: Debiased Contrastive Learning for Sequential Recommendation"

Supercharge Your Model Training

Python-based framework for building and evaluating session-based and session-aware recommender systems.

This is a repository of public data sources for Recommender Systems (RS).

This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.

Codes and Datasets for paper RecSys'20 "SSE-PT: Sequential Recommendation Via Personalized Transformer" and NurIPS'19 "Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers"