This repo relates to the survey paper <Goal-Conditioned Reinforcement Learning: Problems and Solutions>. We collects widely used benchmark environments and conclude a series of research works for g…

This repository contains implementation details and codes for the TrajGAIL

Pytorch code for "Learning Belief Representations for Imitation Learning in POMDPs" (UAI 2019)

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…

Explaining a Reinforcement Learning Agent via Prototyping

Artificial Bee Colony algorithm for Python

Artificial Bee Colony Algorithm in Python.

Hands-on tutorial on ML Fairness

Implementation of a Hyper-Heuristic based on Transformer to solve continuous optimisation problems.

A toolkit for applying LLMs to sensitive, non-public data in offline or restricted environments

Subband averaging kurtogram (SAK), incorporating with dual-tree complex wavelet packet transform (DTCWPT), to improve performance of the fast kurtogram (FK) for rotating machinery fault diagnosis

Compound Fault Diagnosis Dataset of Rotating Machinery

Graphormer is a general-purpose deep learning backbone for molecular modeling.

A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)

Structural Deep Clustering Network

Formulate trained predictors in Gurobi models

Multi-source information fusion deep self-attention reinforcement learning framework for multi-label compound fault recognition

A python program to build ResNet-1D model and DRSN-1D model in keras environment.

This is the code of paper "A Label Information Vector Generative Zero-shot Model for the Diagnosis of Compound Faults"

Source codes for the paper "Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study"

Bearing fault diagnosis model based on MCNN-LSTM

A fault diagnosis method for rotating machinery based on CNN with mixed information

Code for the paper "Smart 'Predict, then Optimize'"

Adaptive large neighbourhood search (and more!) in Python.

[IEEE TKDE | TITS 2023] "Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling" | "Neural Airport Ground Handling"

Attention based model for learning to solve different routing problems