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Sasha Abramowitz
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Mava: A research framework for distributed multi-agent reinforcement learning
A Pretorius, K Tessera, AP Smit, C Formanek, SJ Grimbly, K Eloff, ...
arXiv e-prints, arXiv: 2107.01460, 2021
132021
Jumanji: a diverse suite of scalable reinforcement learning environments in jax
C Bonnet, D Luo, D Byrne, S Surana, V Coyette, P Duckworth, LI Midgley, ...
arXiv preprint arXiv:2306.09884, 2023
12*2023
Efficiently coevolving deep neural networks and data augmentations
S Acton, S Abramowitz, L Toledo, G Nitschke
2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2543-2550, 2020
42020
Towards run-time efficient hierarchical reinforcement learning
S Abramowitz, G Nitschke
2022 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2022
3*2022
Generalisable Agents for Neural Network Optimisation
CR Tilbury, S Abramowitz, RJ de Kock, O Mahjoub, B Rosman, S Hooker, ...
OPT 2023: Optimization for Machine Learning, 2023
2023
Machine Learning in Diagnosing Cervical Spine Injuries
N Kruger, S Abramowitz, G Nitschke
Global Spine Journal 12 (3), 2022
2022
Scalable hierarchical evolution strategies
S Abramowitz
2022
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Articles 1–7