Ghent University Academic Bibliography

BioOSS : a bio-inspired oscillatory state system with spatio-temporal dynamics

Zhongju Yuan (UGent) , Geraint Wiggins and Dick Botteldooren (UGent)

(2025) Advances in Neural Information Processing Systems 38 (NeurIPS 2025). In Advances in neural information processing systems 38.

Add to list

Entropic time schedulers for generative diffusion models

D. Stancevic, Florian Handke (UGent) and L. Ambrogioni

(2025) Advances in Neural Information Processing Systems 38 (NeurIPS 2025). In Advances in neural information processing systems 38.

Add to list

Feedback guidance of diffusion models

Félix Koulischer (UGent) , Florian Handke (UGent) , Johannes Deleu (UGent) , Thomas Demeester (UGent) and L Ambrogioni

(2025) Advances in Neural Information Processing Systems 38 (NeurIPS 2025). In Advances in neural information processing systems 38.

Add to list

Conference Paper
C1
open access

Debiasing synthetic data generated by deep generative models

Alexander Decruyenaere (UGent) , Heidelinde Dehaene (UGent) , Paloma Rabaey (UGent) , Johan Decruyenaere (UGent) , Christiaan Polet (UGent) , Thomas Demeester (UGent) and Stijn Vansteelandt (UGent)

(2024) Advances in Neural Information Processing Systems 37 (NeurIPS 2024). In Advances in Neural Information Processing Systems 37.

Add to list

ABCFair : an adaptable benchmark approach for comparing fairness methods

Marybeth Defrance (UGent) , Maarten Buyl (UGent) and Tijl De Bie (UGent)

(2024) Advances in Neural Information Processing Systems 37 (NeurIPS 2024). In Advances in neural information processing systems 37. p.40145-40163

Add to list

Generative fractional diffusion models

Gabriel Nobis, Maximilian Springenberg, Marco Aversa, Michael Detzel, Rembert Daems (UGent) , Roderick Murray-Smith, Shinichi Nakajima, Sebastian Lapuschkin, Stefano Ermon, Tolga Birdal, et al.

(2024) Advances in Neural Information Processing Systems 37 (NeurIPS 2024). In Advances in neural information processing systems 37. p.25469-25509

Add to list

Conference Paper
C1
open access

GenRL : multimodal-foundation world models for generalization in embodied agents

Pietro Mazzaglia (UGent) , Tim Verbelen (UGent) , Bart Dhoedt (UGent) , A. Courville and S. Rajeswar

(2024) Advances in Neural Information Processing Systems 37 (NeurIPS 2024). In Advances in Neural Information Processing Systems 37.

Add to list

Conference Paper
C1
open access

Contrastive active inference

Pietro Mazzaglia (UGent) , Tim Verbelen (UGent) and Bart Dhoedt (UGent)

(2021) NeurIPS 2021, 5th Conference on Neural Information Processing Systems, Proceedings. In Advances in neural information processing systems 34.

Add to list

High-dimensional multivariate forecasting with low-rank Gaussian Copula processes

David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico and Jan Gasthaus

(2019) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019). In Advances in Neural Information Processing Systems 32.

Add to list

Privacy-preserving classification of personal text messages with secure multi-party computation : an application to hate-speech detection

Devin Reich, Ariel Todoki, Rafael Dowsley, Martine De Cock (UGent) and Anderson Nascimento

(2019) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019). In Advances in Neural Information Processing Systems 32.

Academic Bibliography

BioOSS : a bio-inspired oscillatory state system with spatio-temporal dynamics

Entropic time schedulers for generative diffusion models

Feedback guidance of diffusion models

Debiasing synthetic data generated by deep generative models

ABCFair : an adaptable benchmark approach for comparing fairness methods

Generative fractional diffusion models

GenRL : multimodal-foundation world models for generalization in embodied agents

Contrastive active inference

High-dimensional multivariate forecasting with low-rank Gaussian Copula processes

Privacy-preserving classification of personal text messages with secure multi-party computation : an application to hate-speech detection

Contents

Support

Contact