A Kernel-Based Framework for Learning Graded Relations From Data. - Willem Waegeman; Tapio Pahikkala; Antti Airola; Tapio Salakoski; Michiel Stock; Bernard De Baets (IEEE Trans. Fuzzy Syst., 2012)

Efficient regularized least-squares algorithms for conditional ranking on relational data. - Tapio Pahikkala; Antti Airola; Michiel Stock; Bernard De Baets; Willem Waegeman (Mach. Learn., 2013)

A Two-Step Learning Approach for Solving Full and Almost Full Cold Start Problems in Dyadic Prediction. - Tapio Pahikkala; Michiel Stock; Antti Airola; Tero Aittokallio; Bernard De Baets; Willem Waegeman (ECML/PKDD (2), 2014)

Identification of Functionally Related Enzymes by Learning-to-Rank Methods. - Michiel Stock; Thomas Fober; Eyke Hüllermeier; Serghei Glinca; Gerhard Klebe; Tapio Pahikkala; Antti Airola; Bernard De Baets; Willem Waegeman (IEEE ACM Trans. Comput. Biol. Bioinform., 2014)

Efficient Pairwise Learning Using Kernel Ridge Regression: an Exact Two-Step Method. - Michiel Stock; Tapio Pahikkala; Antti Airola; Bernard De Baets; Willem Waegeman (CoRR, 2016)

Exact and efficient top-K inference for multi-target prediction by querying separable linear relational models. - Michiel Stock; Krzysztof Dembczynski; Bernard De Baets; Willem Waegeman (Data Min. Knowl. Discov., 2016)

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression. - Michiel Stock; Tapio Pahikkala; Antti Airola; Bernard De Baets; Willem Waegeman (Neural Comput., 2018)

Algebraic shortcuts for leave-one-out cross-validation in supervised network inference. - Michiel Stock; Tapio Pahikkala; Antti Airola; Willem Waegeman; Bernard De Baets (Briefings Bioinform., 2020)

Limitations of snapshot hyperspectral cameras to monitor plant response dynamics in stress-free conditions. - Olivier Pieters; Tom De Swaef; Peter Lootens; Michiel Stock; Isabel Roldán-Ruiz; Francis Wyffels (Comput. Electron. Agric., 2020)

Gloxinia - An Open-Source Sensing Platform to Monitor the Dynamic Responses of Plants. - Olivier Pieters; Tom De Swaef; Peter Lootens; Michiel Stock; Isabel Roldán-Ruiz; Francis Wyffels (Sensors, 2020)

Otolith identification using a deep hierarchical classification model. - Michiel Stock; Bac Nguyen; Wouter Courtens; Hilbran Verstraete; Eric W. M. Stienen; Bernard De Baets (Comput. Electron. Agric., 2021)

Disentangling the Information in Species Interaction Networks. - Michiel Stock; Laura Hoebeke; Bernard De Baets (Entropy, 2021)

Practical Equivalent Electrical Circuit Identification for Electrochemical Impedance Spectroscopy Analysis With Gene Expression Programming. - Maxime Van Haeverbeke; Michiel Stock; Bernard De Baets (IEEE Trans. Instrum. Meas., 2021)

Equivalent Electrical Circuits and Their Use Across Electrochemical Impedance Spectroscopy Application Domains. - Maxime Van Haeverbeke; Michiel Stock; Bernard De Baets (IEEE Access, 2022)

BioCCP.jl: collecting coupons in combinatorial biotechnology. - Kirsten Van Huffel; Michiel Stock; Bernard De Baets (Bioinform., 2022)

The Hyperdimensional Transform for Distributional Modelling, Regression and Classification. - Pieter Dewulf; Bernard De Baets; Michiel Stock (CoRR, 2023)

Evaluating the potential of Distribution of Relaxation Times analysis for plant agriculture. - Maxime Van Haeverbeke; Bernard De Baets; Michiel Stock (Comput. Electron. Agric., 2023)

Microelectrode-array-based sensing of bacterial biofilm antibiotic susceptibility using impedance spectroscopy and convolutional neural networks. - Maxime Van Haeverbeke; Charlotte Cums; Thijs Vackier; Dries Braeken; Michiel Stock; Hans Steenackers; Bernard De Baets (BioCAS, 2024)

DepoScope: Accurate phage depolymerase annotation and domain delineation using large language models. - Robby Concha-Eloko; Michiel Stock; Bernard De Baets; Yves Briers; Rafael Sanjuán; Pilar Domingo-Calap; Dimitri Boeckaerts (PLoS Comput. Biol., 2024)

Hyperdimensional computing: A fast, robust, and interpretable paradigm for biological data. - Michiel Stock; Wim Van Criekinge; Dimitri Boeckaerts; Steff Taelman; Maxime Van Haeverbeke; Pieter Dewulf; Bernard De Baets (PLoS Comput. Biol., 2024)

Link Prediction in Stagewise Graphs. - Pieter Dewulf; Michiel Stock; Bernard De Baets (IEEE Trans. Knowl. Data Eng., 2024)

The Hyperdimensional Transform: A Holographic Representation of Functions. - Pieter Dewulf; Michiel Stock; Bernard De Baets (IEEE J. Sel. Top. Signal Process., 2025)

The hyperdimensional transform for distributional modeling, regression and classification. - Pieter Dewulf; Bernard De Baets; Michiel Stock (Neural Comput. Appl., 2025)