Michiel Stock

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 18

Top Topics

Dynamic Response

Kernel Ridge Regression

Relational Models

Top Venues

Comput. Electron. Agric.

IEEE ACM Trans. Comput. Biol. Bioinform.

Publications

Michiel Stock, Dimitri Boeckaerts, Pieter Dewulf, Steff Taelman, Maxime Van Haeverbeke, Wim Van Criekinge, Bernard De Baets
Hyperdimensional computing: a fast, robust and interpretable paradigm for biological data. CoRR (2024)
Pieter Dewulf, Michiel Stock, Bernard De Baets
Link Prediction in Stagewise Graphs. IEEE Trans. Knowl. Data Eng. 36 (7) (2024)
Pieter Dewulf, Michiel Stock, Bernard De Baets
The Hyperdimensional Transform: a Holographic Representation of Functions. CoRR (2023)
Maxime Van Haeverbeke, Bernard De Baets, Michiel Stock
Evaluating the potential of Distribution of Relaxation Times analysis for plant agriculture. Comput. Electron. Agric. 213 (2023)
Pieter Dewulf, Bernard De Baets, Michiel Stock
The Hyperdimensional Transform for Distributional Modelling, Regression and Classification. CoRR (2023)
Kirsten Van Huffel, Michiel Stock, Bernard De Baets
BioCCP.jl: collecting coupons in combinatorial biotechnology. Bioinform. 38 (4) (2022)
Maxime Van Haeverbeke, Michiel Stock, Bernard De Baets
Equivalent Electrical Circuits and Their Use Across Electrochemical Impedance Spectroscopy Application Domains. IEEE Access 10 (2022)
Michiel Stock, Bac Nguyen, Wouter Courtens, Hilbran Verstraete, Eric W. M. Stienen, Bernard De Baets
Otolith identification using a deep hierarchical classification model. Comput. Electron. Agric. 180 (2021)
Michiel Stock, Laura Hoebeke, Bernard De Baets
Disentangling the Information in Species Interaction Networks. Entropy 23 (6) (2021)
Maxime Van Haeverbeke, Michiel Stock, Bernard De Baets
Practical Equivalent Electrical Circuit Identification for Electrochemical Impedance Spectroscopy Analysis With Gene Expression Programming. IEEE Trans. Instrum. Meas. 70 (2021)
Olivier Pieters, Tom De Swaef, Peter Lootens, Michiel Stock, Isabel Roldán-Ruiz, Francis Wyffels
Gloxinia - An Open-Source Sensing Platform to Monitor the Dynamic Responses of Plants. Sensors 20 (11) (2020)
Olivier Pieters, Tom De Swaef, Peter Lootens, Michiel Stock, Isabel Roldán-Ruiz, Francis Wyffels
Limitations of snapshot hyperspectral cameras to monitor plant response dynamics in stress-free conditions. Comput. Electron. Agric. 179 (2020)
Michiel Stock, Tapio Pahikkala, Antti Airola, Willem Waegeman, Bernard De Baets
Algebraic shortcuts for leave-one-out cross-validation in supervised network inference. Briefings Bioinform. 21 (1) (2020)
Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman
A Comparative Study of Pairwise Learning Methods based on Kernel Ridge Regression. CoRR (2018)
Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman
A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression. Neural Comput. 30 (8) (2018)
Michiel Stock, Krzysztof Dembczynski, Bernard De Baets, Willem Waegeman
Exact and efficient top-K inference for multi-target prediction by querying separable linear relational models. Data Min. Knowl. Discov. 30 (5) (2016)
Michiel Stock, Krzysztof Dembczynski, Bernard De Baets, Willem Waegeman
Exact and efficient top-K inference for multi-target prediction by querying separable linear relational models. CoRR (2016)
Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman
Efficient Pairwise Learning Using Kernel Ridge Regression: an Exact Two-Step Method. CoRR (2016)
Michiel Stock, Thomas Fober, Eyke Hüllermeier, Serghei Glinca, Gerhard Klebe, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman
Identification of Functionally Related Enzymes by Learning-to-Rank Methods. IEEE ACM Trans. Comput. Biol. Bioinform. 11 (6) (2014)
Tapio Pahikkala, Michiel Stock, Antti Airola, Tero Aittokallio, Bernard De Baets, Willem Waegeman
A Two-Step Learning Approach for Solving Full and Almost Full Cold Start Problems in Dyadic Prediction. ECML/PKDD (2) (2014)
Tapio Pahikkala, Michiel Stock, Antti Airola, Tero Aittokallio, Bernard De Baets, Willem Waegeman
A two-step learning approach for solving full and almost full cold start problems in dyadic prediction. CoRR (2014)
Michiel Stock, Thomas Fober, Eyke Hüllermeier, Serghei Glinca, Gerhard Klebe, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman
Identification of functionally related enzymes by learning-to-rank methods. CoRR (2014)
Tapio Pahikkala, Antti Airola, Michiel Stock, Bernard De Baets, Willem Waegeman
Efficient regularized least-squares algorithms for conditional ranking on relational data. Mach. Learn. 93 (2-3) (2013)
Willem Waegeman, Tapio Pahikkala, Antti Airola, Tapio Salakoski, Michiel Stock, Bernard De Baets
A Kernel-Based Framework for Learning Graded Relations From Data. IEEE Trans. Fuzzy Syst. 20 (6) (2012)
Tapio Pahikkala, Antti Airola, Michiel Stock, Bernard De Baets, Willem Waegeman
Efficient Regularized Least-Squares Algorithms for Conditional Ranking on Relational Data CoRR (2012)
Willem Waegeman, Tapio Pahikkala, Antti Airola, Tapio Salakoski, Michiel Stock, Bernard De Baets
A kernel-based framework for learning graded relations from data CoRR (2011)