Implementation of different Policy Gradient Algorithms

Template Tugas Akhir IF ITB dengan LaTeX

Graph Neural Network Library for PyTorch

A parser for Google Scholar, written in Python

Code for my PAKDD-2019, Distance2Pre: Personalized Spatial Preference for Next Point-of-Interest Prediction

Dataset Batch(offline) Reinforcement Learning for recommender system

Collection of reinforcement learning algorithms

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼

This repository accompanies our research paper titled "An LLM-based Recommender System Environment".

This code was used for a scientific publication where we we recreated a Deep Embedded Clustering model on a populations of ICU patients. We tested the model's generalisability onto a population of …

PyTorch Implementation of MADDPG (Lowe et. al. 2017)

The official repository for "Multi-Scale Protein Structure Modelling with Geometric Graph U-Nets"

Code for paper "GETNext: Trajectory Flow Map Enhanced Transformer for Next POI Recommendation"

Source code for Knowledge Transfer via Pre-training for Recommendation: A Review and Prospect

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

Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender systems

An Efficient and Unified Benchmark for GNN-based Recommendation.

Implement a reasoning LLM in PyTorch from scratch, step by step

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..

[SIGSPATIAL 2023] Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation

Platonic Transformers: A Solid Choice For Equivariance

Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.