Herke van Hoof

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 80

Top Venues

Darmstadt University of Technology, Germany (PHD)

Education History

Darmstadt University of Technology, Germany

PHD

Publications

David Kuric, Guillermo Infante, Vicenç Gómez, Anders Jonsson, Herke van Hoof
Planning with a Learned Policy Basis to Optimally Solve Complex Tasks. ICAPS (2024)
Robert T. Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. AAMAS (2024)
Guillermo Infante, David Kuric, Anders Jonsson, Vicenç Gómez, Herke van Hoof
Planning with a Learned Policy Basis to Optimally Solve Complex Tasks. CoRR (2024)
Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof, Maarten de Rijke
Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems. SIGIR (2024)
Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof, Maarten de Rijke
Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems. CoRR (2024)
Tim Bakker, Herke van Hoof, Max Welling
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. ECML/PKDD (1) (2023)
Robert Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. CoRR (2023)
Nutan Chen, Walterio W. Mayol-Cuevas, Maximilian Karl, Elie Aljalbout, Andy Zeng, Aurelio Cortese, Wolfram Burgard, Herke van Hoof
Editorial: Language, affordance and physics in robot cognition and intelligent systems. Frontiers Robotics AI 10 (2023)
Blazej Manczak, Jan Viebahn, Herke van Hoof
Hierarchical Reinforcement Learning for Power Network Topology Control. CoRR (2023)
Tim Bakker, Herke van Hoof, Max Welling
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. CoRR (2023)
David Kuric, Herke van Hoof
Reusable Options through Gradient-based Meta Learning. Trans. Mach. Learn. Res. 2023 (2023)
Jan Wöhlke, Felix Schmitt, Herke van Hoof
Learning Hierarchical Planning-Based Policies from Offline Data. ECML/PKDD (4) (2023)
Qi Wang, Marco Federici, Herke van Hoof
Bridge the Inference Gaps of Neural Processes via Expectation Maximization. ICLR (2023)
Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling
Multi-Agent MDP Homomorphic Networks. ICLR (2022)
Qi Wang, Herke van Hoof
Learning Expressive Meta-Representations with Mixture of Expert Neural Processes. NeurIPS (2022)
Erik Jenner, Herke van Hoof, Adam Gleave
Calculus on MDPs: Potential Shaping as a Gradient. CoRR (2022)
Qi Wang, Herke van Hoof
Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search. ICML (2022)
Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Will Zeng, Piero Zappi
Neural Topological Ordering for Computation Graphs. NeurIPS (2022)
Jan Wöhlke, Felix Schmitt, Herke van Hoof
Value Refinement Network (VRN). IJCAI (2022)
David Kuric, Herke van Hoof
Reusable Options through Gradient-based Meta Learning. CoRR (2022)
Alexander Long, Alan Blair, Herke van Hoof
Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation. CoRR (2022)
Charul Giri, Ole-Christoffer Granmo, Herke van Hoof, Christian D. Blakely
Logic-based AI for Interpretable Board Game Winner Prediction with Tsetlin Machine. CoRR (2022)
Niklas Höpner, Ilaria Tiddi, Herke van Hoof
Leveraging Class Abstraction for Commonsense Reinforcement Learning via Residual Policy Gradient Methods. IJCAI (2022)
Tessa van der Heiden, Herke van Hoof, Efstratios Gavves, Christoph Salge
Reliably Re-Acting to Partner's Actions with the Social Intrinsic Motivation of Transfer Empowerment. CoRR (2022)
Charul Giri, Ole-Christoffer Granmo, Herke van Hoof, Christian D. Blakely
Logic-based AI for Interpretable Board Game Winner Prediction with Tsetlin Machine. IJCNN (2022)
Wouter Kool, Herke van Hoof, Joaquim A. S. Gromicho, Max Welling
Deep Policy Dynamic Programming for Vehicle Routing Problems. CPAIOR (2022)
Alexander Long, Alan Blair, Herke van Hoof
Fast and Data Efficient Reinforcement Learning from Pixels via Non-parametric Value Approximation. AAAI (2022)
Masoud Mansoury, Bamshad Mobasher, Herke van Hoof
Exposure-Aware Recommendation using Contextual Bandits. CoRR (2022)
Niklas Höpner, Ilaria Tiddi, Herke van Hoof
Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods. CoRR (2022)
Jan Wöhlke, Felix Schmitt, Herke van Hoof
Hierarchies of Planning and Reinforcement Learning for Robot Navigation. CoRR (2021)
Dmitrii Krasheninnikov, Rohin Shah, Herke van Hoof
Combining Reward Information from Multiple Sources. CoRR (2021)
Wouter Kool, Herke van Hoof, Joaquim A. S. Gromicho, Max Welling
Deep Policy Dynamic Programming for Vehicle Routing Problems. CoRR (2021)
Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling
Multi-Agent MDP Homomorphic Networks. CoRR (2021)
Yijie Zhang, Herke van Hoof
Deep Coherent Exploration for Continuous Control. ICML (2021)
Qi Wang, Herke van Hoof
Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models. CoRR (2021)
Shihan Wang, Chao Zhang, Ben J. A. Kröse, Herke van Hoof
Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator. J. Medical Syst. 45 (12) (2021)
Jan Wöhlke, Felix Schmitt, Herke van Hoof
Hierarchies of Planning and Reinforcement Learning for Robot Navigation. ICRA (2021)
Susan Amin, Maziar Gomrokchi, Harsh Satija, Herke van Hoof, Doina Precup
A Survey of Exploration Methods in Reinforcement Learning. CoRR (2021)
Qi Wang, Herke van Hoof
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables. ICML (2020)
Tessa van der Heiden, Florian Mirus, Herke van Hoof
Social Navigation with Human Empowerment Driven Deep Reinforcement Learning. ICANN (2) (2020)
Wouter Kool, Herke van Hoof, Max Welling
Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement. J. Mach. Learn. Res. 21 (2020)
Wouter Kool, Herke van Hoof, Max Welling
Estimating Gradients for Discrete Random Variables by Sampling without Replacement. ICLR (2020)
Wouter Kool, Herke van Hoof, Max Welling
Estimating Gradients for Discrete Random Variables by Sampling without Replacement. CoRR (2020)
Joris Mollinga, Herke van Hoof
An Autonomous Free Airspace En-route Controller using Deep Reinforcement Learning Techniques. CoRR (2020)
Jin Huang, Harrie Oosterhuis, Maarten de Rijke, Herke van Hoof
Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems. RecSys (2020)
Tim Bakker, Herke van Hoof, Max Welling
Experimental design for MRI by greedy policy search. CoRR (2020)
Tessa van der Heiden, Christoph Salge, Efstratios Gavves, Herke van Hoof
Robust Multi-Agent Reinforcement Learning with Social Empowerment for Coordination and Communication. CoRR (2020)
Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. NeurIPS (2020)
Tim Bakker, Herke van Hoof, Max Welling
Experimental design for MRI by greedy policy search. NeurIPS (2020)
Tessa van der Heiden, Christian Weiss, Naveen Shankar Nagaraja, Herke van Hoof
Social navigation with human empowerment driven reinforcement learning. CoRR (2020)
Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen V. Hindriks, Holger H. Hoos, Hayley Hung, Catholijn M. Jonker, Christof Monz, Mark A. Neerincx, Frans A. Oliehoek, Henry Prakken, Stefan Schlobach, Linda C. van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, Max Welling
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer 53 (8) (2020)
Jan Wöhlke, Felix Schmitt, Herke van Hoof
A Performance-Based Start State Curriculum Framework for Reinforcement Learning. AAMAS (2020)
Qi Wang, Herke van Hoof
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables. CoRR (2020)
Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. CoRR (2020)
Sanjay Thakur, Herke van Hoof, Gunshi Gupta, David Meger
Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales. CoRR (2019)
Sanjay Thakur, Herke van Hoof, Juan Camilo Gamboa Higuera, Doina Precup, David Meger
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks. ICRA (2019)
Sandeep Manjanna, Herke van Hoof, Gregory Dudek
Reinforcement Learning with Non-uniform State Representations for Adaptive Search. CoRR (2019)
Wouter Kool, Herke van Hoof, Max Welling
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement. ICML (2019)
Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau
Deep Generative Modeling of LiDAR Data. IROS (2019)
Wouter Kool, Herke van Hoof, Max Welling
Buy 4 REINFORCE Samples, Get a Baseline for Free! DeepRLStructPred@ICLR (2019)
Wouter Kool, Herke van Hoof, Max Welling
Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement. CoRR (2019)
Wenling Shang, Douwe van der Wal, Herke van Hoof, Max Welling
Stochastic Activation Actor Critic Methods. ECML/PKDD (3) (2019)
Sanjay Thakur, Herke van Hoof, Juan Camilo Gamboa Higuera, Doina Precup, David Meger
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks. CoRR (2019)
Wouter Kool, Herke van Hoof, Max Welling
Attention, Learn to Solve Routing Problems! ICLR (Poster) (2019)
Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau
Deep Generative Modeling of LiDAR Data. CoRR (2018)
Scott Fujimoto, Herke van Hoof, David Meger
Addressing Function Approximation Error in Actor-Critic Methods. CoRR (2018)
Matthew J. A. Smith, Herke van Hoof, Joelle Pineau
An Inference-Based Policy Gradient Method for Learning Options. ICML (2018)
Sandeep Manjanna, Herke van Hoof, Gregory Dudek
Reinforcement Learning with Non-uniform State Representations for Adaptive Search. SSRR (2018)
Scott Fujimoto, Herke van Hoof, David Meger
Addressing Function Approximation Error in Actor-Critic Methods. ICML (2018)
Victor Barbaros, Herke van Hoof, Abbas Abdolmaleki, David Meger
Eager and Memory-Based Non-Parametric Stochastic Search Methods for Learning Control. ICRA (2018)
Yue Dong, Yikang Shen, Eric Crawford, Herke van Hoof, Jackie Chi Kit Cheung
BanditSum: Extractive Summarization as a Contextual Bandit. EMNLP (2018)
Yue Dong, Yikang Shen, Eric Crawford, Herke van Hoof, Jackie Chi Kit Cheung
BanditSum: Extractive Summarization as a Contextual Bandit. CoRR (2018)
Sandeep Manjanna, Herke van Hoof, Gregory Dudek
Policy Search on Aggregated State Space for Active Sampling. ISER (2018)
Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, Masashi Sugiyama
Policy Search with High-Dimensional Context Variables. AAAI (2017)
Herke van Hoof, Daniel Tanneberg, Jan Peters
Generalized exploration in policy search. Mach. Learn. 106 (9-10) (2017)
Herke van Hoof, Gerhard Neumann, Jan Peters
Non-parametric Policy Search with Limited Information Loss. J. Mach. Learn. Res. 18 (2017)
Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, Masashi Sugiyama
Policy Search with High-Dimensional Context Variables. CoRR (2016)
Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann
Probabilistic inference for determining options in reinforcement learning. Mach. Learn. 104 (2-3) (2016)
Herke van Hoof, Nutan Chen, Maximilian Karl, Patrick van der Smagt, Jan Peters
Stable reinforcement learning with autoencoders for tactile and visual data. IROS (2016)
Zhengkun Yi, Roberto Calandra, Filipe Veiga, Herke van Hoof, Tucker Hermans, Yilei Zhang, Jan Peters
Active tactile object exploration with Gaussian processes. IROS (2016)
Herke van Hoof, Jan Peters, Gerhard Neumann
Learning of Non-Parametric Control Policies with High-Dimensional State Features. AISTATS (2015)
Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke van Hoof, Jan Peters
Towards learning hierarchical skills for multi-phase manipulation tasks. ICRA (2015)
Herke van Hoof, Tucker Hermans, Gerhard Neumann, Jan Peters
Learning robot in-hand manipulation with tactile features. Humanoids (2015)
Filipe Veiga, Herke van Hoof, Jan Peters, Tucker Hermans
Stabilizing novel objects by learning to predict tactile slip. IROS (2015)
Herke van Hoof, Oliver Kroemer, Jan Peters
Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments. IEEE Trans. Robotics 30 (5) (2014)
Bastian Bischoff, Duy Nguyen-Tuong, Herke van Hoof, Andrew McHutchon, Carl E. Rasmussen, Alois C. Knoll, Jan Peters, Marc Peter Deisenroth
Policy search for learning robot control using sparse data. ICRA (2014)
Oliver Kroemer, Herke van Hoof, Gerhard Neumann, Jan Peters
Learning to predict phases of manipulation tasks as hidden states. ICRA (2014)
Herke van Hoof, Oliver Kroemer, Jan Peters
Probabilistic interactive segmentation for anthropomorphic robots in cluttered environments. Humanoids (2013)
Herke van Hoof, Oliver Kroemer, Heni Ben Amor, Jan Peters
Maximally informative interaction learning for scene exploration. IROS (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Herke van Hoof