Hoogendoorn, Mark

14 publications

TMLR 2025 Learning Task-Aware Abstract Representations for Meta-Reinforcement Learning Louk van Remmerden, Zhao Yang, Shujian Yu, Mark Hoogendoorn, Vincent Francois-Lavet

TMLR 2025 ModernTCN Revisited: A Critical Look at the Experimental Setup in General Time Series Analysis Önder Akacik, Mark Hoogendoorn

TMLR 2025 Relative Phase Equivariant Deep Neural Systems for Physical Layer Communications Arwin Gansekoele, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei

ICLR 2025 Start Smart: Leveraging Gradients for Enhancing Mask-Based XAI Methods Buelent Uendes, Shujian Yu, Mark Hoogendoorn

TMLR 2024 Wavelet Networks: Scale-Translation Equivariant Learning from Raw Time-Series David W. Romero, Erik J Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

ICLR 2023 Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN David M Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-jakob Sonke

ICLR 2022 CKConv: Continuous Kernel Convolution for Sequential Data David W. Romero, Anna Kuzina, Erik J Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn

ICLR 2022 FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J Bekkers, Mark Hoogendoorn, Jan van Gemert

MLJ 2022 Planning for Potential: Efficient Safe Reinforcement Learning Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen

IJCAI 2022 Reinforcement Learning with Option Machines Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen

ICML 2020 Attentive Group Equivariant Convolutional Networks David Romero, Erik Bekkers, Jakub Tomczak, Mark Hoogendoorn

ICLR 2020 Co-Attentive Equivariant Neural Networks: Focusing Equivariance on Transformations Co-Occurring in Data David W. Romero, Mark Hoogendoorn

IJCAI 2011 Modeling Situation Awareness in Human-like Agents Using Mental Models Mark Hoogendoorn, Rianne van Lambalgen, Jan Treur

IJCAI 2007 Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks Mark Hoogendoorn