Demeester, Thomas

16 publications

ICLR 2025 Dynamic Negative Guidance of Diffusion Models Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni

NeurIPS 2025 Feedback Guidance of Diffusion Models Felix Koulischer, Florian Handke, Johannes Deleu, Thomas Demeester, Luca Ambrogioni

NeurIPSW 2024 Anchored Optimization and Contrastive Revisions: Addressing Reward Hacking in Alignment Karel D'Oosterlinck, Winnie Xu, Chris Develder, Thomas Demeester, Amanpreet Singh, Christopher Potts, Douwe Kiela, Shikib Mehri

NeurIPS 2024 Debiasing Synthetic Data Generated by Deep Generative Models Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Thomas Demeester, Stijn Vansteelandt

NeurIPSW 2024 Dynamic Negative Guidance of Diffusion Models: Towards Immediate Content Removal Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni

NeurIPSW 2024 From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding Henri Arno, Paloma Rabaey, Thomas Demeester

UAI 2024 The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester

NeurIPSW 2023 Accelerating Hierarchical Associative Memory: A Deep Equilibrium Approach Cédric Goemaere, Johannes Deleu, Thomas Demeester

NeurIPSW 2023 Exploring the Temperature-Dependent Phase Transition in Modern Hopfield Networks Felix Koulischer, Cédric Goemaere, Tom Van Der Meersch, Johannes Deleu, Thomas Demeester

NeurIPSW 2023 Synthetic Data: Can We Trust Statistical Estimators? Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester

NeurIPSW 2023 Training a Hopfield Variational Autoencoder with Equilibrium Propagation Tom Van Der Meersch, Johannes Deleu, Thomas Demeester

NeurIPSW 2022 Neural Bayesian Network Understudy Paloma Rabaey, Cedric De Boom, Thomas Demeester

NeurIPS 2022 TempEL: Linking Dynamically Evolving and Newly Emerging Entities Klim Zaporojets, Lucie-Aimée Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder, Isabelle Augenstein

AAAI 2020 System Identification with Time-Aware Neural Sequence Models Thomas Demeester

NeurIPS 2018 DeepProbLog: Neural Probabilistic Logic Programming Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt

UAI 2017 Adversarial Sets for Regularising Neural Link Predictors Pasquale Minervini, Thomas Demeester, Tim Rocktäschel, Sebastian Riedel