← Authors

Herke van Hoof

20 papers · 2015–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (39) πŸŒ‰ Interdisciplinary Bridge πŸ† Grand Slam πŸ‘‘ Triple Crown ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (86) πŸ’Ž Century Club (20) πŸ”₯ Unstoppable (7)

Conferences

ICLR (4) ICML (4) NIPS (4) AAAI (2) IJCAI (2) JMLR (2) AISTATS (1) EMNLP (1)

Top co-authors

Max Welling (7) Qi Wang (4) Wouter Kool (4) Elise van der Pol (2) Gerhard Neumann (2) Ilaria Tiddi (2) Jan Peters (2) Yijie Zhang (1) Wonseok Jeon (1) Marco Federici (1)

Keywords

policy search (2) policy gradient (2) graph neural network (2) stochastic process (2) reinforcement learning (2) deep reinforcement learning (2) continuous control (2) neural process (2) neural network (2) stochastic beam search (2) variational inference (2) probabilistic inference (1) sample efficiency (1) uncertainty quantification (1) combinatorial optimization (1) robot navigation (1) instruction following (1) policy optimization (1) representation learning (1) policy learning (1)

Papers

Data Augmentation for Instruction Following Policies via Trajectory Segmentation AAAI 2025
Bridge the Inference Gaps of Neural Processes via Expectation Maximization ICLR 2023
Fast and Data Efficient Reinforcement Learning from Pixels via Non-parametric Value Approximation AAAI 2022
Neural Topological Ordering for Computation Graphs NIPS 2022
Learning Expressive Meta-Representations with Mixture of Expert Neural Processes NIPS 2022
Multi-Agent MDP Homomorphic Networks ICLR 2022
Value Refinement Network (VRN) IJCAI 2022
Leveraging Class Abstraction for Commonsense Reinforcement Learning via Residual Policy Gradient Methods IJCAI 2022
Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search ICML 2022
Deep Coherent Exploration for Continuous Control ICML 2021
Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement JMLR 2020
Experimental design for MRI by greedy policy search NIPS 2020
Estimating Gradients for Discrete Random Variables by Sampling without Replacement ICLR 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables ICML 2020
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning NIPS 2020
Attention, Learn to Solve Routing Problems! ICLR 2019
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement ICML 2019
BanditSum: Extractive Summarization as a Contextual Bandit EMNLP 2018
Non-parametric Policy Search with Limited Information Loss JMLR 2017
Learning of Non-Parametric Control Policies with High-Dimensional State Features AISTATS 2015