Toolbox-lijst

A python repository for Automated MRI quantification of volumetric per muscle fat-fractions in the proximal leg of patients with muscular dystrophies

The toolbox enables cost-efficient optimization of manufacturing process design parameters. It achieves this through data-efficient methodologies for sequential experiment design, streamlining and enhancing optimization processes..

Adhesive Bonding Optimization Toolbox with Uncertainty and Feasibility constraints

A web application for exploring and selecting datasets based on informed criteria, designed to support recommender system experiments.

The all-in-one toolkit for multi-agent experiments on emergent communication

Bootstrapped Dual Policy Iteration: sample-efficient model-free RL with discrete actions

Interactive random forest local explainability toolbox

Local explainability tool for Random (Survival) Forest predictions

A Python package for fairness metrics in language models

Active learning based workflow for automated 3D-EM segmentation

A software for evaluating model calibration, volume bias and a correlation between the two

Exposing Algorithmic Bias with Canonical Sets

Loading and scrubbing of data XML files exported from Canon OCT-A1 machine.

Library for treatment effect analysis

Code and analysis framework for studying how LLMs trade off financial rewards against user inconvenience.

Solver for executing constraint Decision Model and Notation (cDMN) models.

‘cEASEr’ and ‘Add-EASEr’ algorithms, as presented in the publication ‘Closed-Form Models for Collaborative Filtering with Side-Information’

A procedure for calculating confidence intervals for the eigendecomposition of covariance matrices.

Library for unsupervised clustering of  large data sets of T cell receptor sequences.

Library for semi-supervised clustering using pairwise constraints

(PyPI-installable) Python package for time series anomaly detection.

a Constraint Programming and Modeling library in Python, based on numpy, with direct solver access.

crepes-weighted extends crepes by adding support for weighted conformal prediction and predictive systems

A library implementing the DASF algorithmic framework for solving linear signal or feature fusion optimization problems in a distributed setting, where different signal- or feature dimensions of each sample are spread across the nodes of a network.

A Python-based deep learning framework for multi-target prediction

Deep Learning and Probabilistic Logic Programming

DeepStochLog is a neuro-symbolic framework that combines grammars, logic, probabilities and neural networks. 

A Python library to  implement deep learning pipelines for medical applications using convolutional neural networks (CNNs).

Interface for user-friendly and interactive execution of DMN

API for user-friendly and flexible execution of DMN.

Time series distances (DTW, ED), clustering and subsequence search

‘Dual Bandit’ algorithm, as presented in the publication ‘Joint Policy-Value Learning for Recommendation’

DUST, the Distributed Uniform STreaming library for distributed artificial intelligence

A simulation engine for dynamic models of single-cell transcriptomics data.

A Python/C++ library which provides a centralized repository with analytical and numerical methods to study/model game theoretical problems under the Evolutionary Game Theory (EGT) framework.

Library for evaluation of graph representation learning methods.

Algorithm for the detection of “events of interest” in time series

A self-organizing map based approach for the automated analysis of cytometry data.

Library for shapelet extraction from time series using a genetic algorithm.

Library for Bayesian optimization and active learning (only for Tensorflow 1.x)

Multi-objective hyperparameter optimization with performance uncertainty

A gym environment for a compartment model modelling the first COVID wave in Belgium.

A software suite and a web application for labelling and managing HSI datasets, and training different deep learning models on these datasets.

A multi-inference engine for the FO(.) knowledge representation language

Library for the generation of human-comprehensible binary feature representations from nodes within a knowledge graphs

A decision support tool using knowledge expressed in the FO(.) language.

This toolbox enforces your Pytorch model to have correct local post-hoc explanations

Library for (anatomical) landmark detection in images

Sensor fusion technique for laser-based 3D print monitoring, including scripts for spatiotemporal data synchronization;

Library for discovery of inconsistencies and outliers

Code for learning local image descriptors with autoencoedrs and variational autoencoders

Long Short-term Cognitive Network (LSTCN) model for time series forecasting

Scalable Bayesian factorization with high-dimensional side information using MCMC

Toolbox for solving systems of multivariate polynomial equations and rectangular multiparameter eigenvalue problems

Library for multi-objective reinforcement learning environments

Open source Python library for developing and comparing multi-objective multi-agent reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments, as well as a standard set of environments compliant with that API.

Gym Reinforcement Learning environment for ROS robots, with MoveIT planner and safety layer

Toolbox containing several MAS environments, allowing to compare different algorithms

Task and motion planning workflow with optimistic reinforcement learning-based skill insertions

Solver for executing probabilistic Decision Model and Notation (pDMN) models.

Schema Mapping and Query Rewriting system for personalized decentralized data storage pods

Code for calibration of trained segmentation models using platt scaling, fine tuning and simple convolutional auxiliary networks 

Library for feature selection 

Code to perform super-resolution on structural MRI using fine-tuned convolutional neural networks.

Probabilistic Logic Programming

A Library for data analysis using STAD (Simplified Topological Abstraction of Data) networks.

Algorithm for classification of kidney transplant pathology

Recursive Gradient Attack on Privacy

RobBERT is the state-of-the-art Dutch BERT language model.

Library for creating relational graph convolutional Network embeddings 

Package designed for analysis and exploration of single-cell RNA-seq datasets.

Using SHACL constraint language for a novel use of shapes, by which a set of shapes is used to extract a subgraph from an RDF graph, the so-called shape fragment.

Reinforcement learning agents as a web service

Multiobjective Ranking and Selection Using Stochastic Kriging

Real-world extreme edge prototype to train an LLM (Large Language Model) on personal data in an extreme edge network at people’s home.

Fast and accurate machine learning model for small molecules

Visualisation technique to display topological information in high-dimensional data

Tool for hardware-mapping design space exploration of deep learning accelerators

Toolbox for automated failure diagnosis using ontology-based knowledge graphs for heterogenous industrial machines

Code for deep image hashing based on twin-bottleneck architecture with variational autoencoders.

A reproducible research repository for tensor computations

An autoencoder-based change point detection algorithm for time series data that uses a TIme-Invariant Representation (TIRE).

Library to unify temporal series with hierarchical semantic information through dynamic path aggregation on tree-structured data

Library for Bayesian optimization and active learning

Python package for automatically constructing features from multi-view time series data.

Veritas is a versatile verification tool for tree ensembles. You can use Veritas to generate adversarial examples, check robustness, find dominant attributes or simply ask domain specific questions about your model.

Library for context-aware visualization recommender systems

Notebooks for a practical session on training a digit classifier and using it to solve visual Sudok's

Jupyter notebook and Python library to demonstrate the use of word prediction using deep learning as an aid in historical linguistics.

Hardware architecture (HW)-mapping design space exploration (DSE) framework for deep learning (DL) accelerators.