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2020 – today
- 2025
[c5]Calarina Muslimani, Bram Grooten, Deepak Ranganatha Sastry Mamillapalli, Mykola Pechenizkiy, Decebal Constantin Mocanu, Matthew E. Taylor:
Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity. AAMAS 2025: 2687-2689- [i11]Bram Grooten, Farid Hasanov, Chenxiang Zhang, Qiao Xiao, Boqian Wu, Zahra Atashgahi, Ghada Sokar, Shiwei Liu, Lu Yin, Elena Mocanu
, Mykola Pechenizkiy, Decebal Constantin Mocanu:
NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling. CoRR abs/2505.17909 (2025) - [i10]Tristan Tomilin, Luka van den Boogaard, Samuel Garcin, Bram Grooten, Meng Fang, Mykola Pechenizkiy:
MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning. CoRR abs/2506.14990 (2025) - [i9]Bram Grooten, Patrick MacAlpine, Kaushik Subramanian, Peter Stone, Peter R. Wurman:
Out-of-Distribution Generalization with a SPARC: Racing 100 Unseen Vehicles with a Single Policy. CoRR abs/2511.09737 (2025) - [i8]Wieger Wesselink, Bram Grooten, Huub van de Wetering, Qiao Xiao, Decebal Constantin Mocanu:
Batch Matrix-form Equations and Implementation of Multilayer Perceptrons. CoRR abs/2511.11918 (2025) - 2024
- [c4]Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu:
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. AAMAS 2024: 733-742 - [c3]Bram Grooten:
Large Learning Agents: Towards Continually Aligned Robots with Scale in RL. AAMAS 2024: 2746-2748 - [i7]Calarina Muslimani, Bram Grooten, Deepak Ranganatha Sastry Mamillapalli, Mykola Pechenizkiy, Decebal Constantin Mocanu, Matthew E. Taylor:
Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity. CoRR abs/2406.06495 (2024) - [i6]Wieger Wesselink, Bram Grooten, Qiao Xiao, Cassio de Campos, Mykola Pechenizkiy:
Nerva: a Truly Sparse Implementation of Neural Networks. CoRR abs/2407.17437 (2024) - [i5]Camiel Oerlemans, Bram Grooten, Michiel Braat, Alaa Alassi, Emilia Silvas, Decebal Constantin Mocanu:
LiMTR: Time Series Motion Prediction for Diverse Road Users through Multimodal Feature Integration. CoRR abs/2410.15819 (2024) - 2023
- [c2]Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu:
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. AAMAS 2023: 1932-1941 - [c1]Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor:
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. NeurIPS 2023 - [i4]Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu:
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. CoRR abs/2302.06548 (2023) - [i3]Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor:
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. CoRR abs/2306.12230 (2023) - [i2]Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu:
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. CoRR abs/2312.15339 (2023) - 2022
- [i1]Bram Grooten, Jelle Wemmenhove, Maurice Poot, Jim Portegies:
Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for Hanabi. CoRR abs/2203.11656 (2022)
Coauthor Index
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