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2020 – today
- 2023
[j3]Andries P. Smit
, Herman A. Engelbrecht, Willie Brink, Arnu Pretorius:
Scaling multi-agent reinforcement learning to full 11 versus 11 simulated robotic football. Auton. Agents Multi Agent Syst. 37(1): 20 (2023)- [c9]Claude Formanek, Asad Jeewa, Jonathan P. Shock, Arnu Pretorius:
Off-the-Grid MARL: Datasets and Baselines for Offline Multi-Agent Reinforcement Learning. AAMAS 2023: 2442-2444 - [i17]Claude Formanek, Asad Jeewa, Jonathan P. Shock, Arnu Pretorius:
Off-the-Grid MARL: a Framework for Dataset Generation with Baselines for Cooperative Offline Multi-Agent Reinforcement Learning. CoRR abs/2302.00521 (2023) - [i16]Claude Formanek, Callum Rhys Tilbury, Jonathan P. Shock, Kale-ab Tessera, Arnu Pretorius:
Reduce, Reuse, Recycle: Selective Reincarnation in Multi-Agent Reinforcement Learning. CoRR abs/2304.00977 (2023) - 2022
- [c8]Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts:
Robust and Scalable SDE Learning: A Functional Perspective. ICLR 2022 - [c7]Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius:
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL. NeurIPS 2022 - [c6]Matthew Morris, Thomas D. Barrett, Arnu Pretorius:
Universally Expressive Communication in Multi-Agent Reinforcement Learning. NeurIPS 2022 - [i15]Matthew Morris, Thomas D. Barrett, Arnu Pretorius:
Universally Expressive Communication in Multi-Agent Reinforcement Learning. CoRR abs/2206.06758 (2022) - [i14]Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius:
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL. CoRR abs/2209.10485 (2022) - 2021
- [i13]Arnu Pretorius, Kale-ab Tessera, Andries P. Smit, Claude Formanek, St John Grimbly, Kevin Eloff, Siphelele Danisa, Lawrence Francis, Jonathan P. Shock, Herman Kamper, Willie Brink, Herman A. Engelbrecht, Alexandre Laterre, Karim Beguir:
Mava: a research framework for distributed multi-agent reinforcement learning. CoRR abs/2107.01460 (2021) - [i12]Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts:
Robust and Scalable SDE Learning: A Functional Perspective. CoRR abs/2110.05167 (2021) - [i11]Kevin Eloff, Arnu Pretorius, Okko Räsänen, Herman A. Engelbrecht, Herman Kamper:
Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel. CoRR abs/2111.02827 (2021) - [i10]Ibrahim Salihu Yusuf, Kale-ab Tessera, Thomas Tumiel, Sella Nevo, Arnu Pretorius:
On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa. CoRR abs/2111.03904 (2021) - [i9]St John Grimbly, Jonathan P. Shock, Arnu Pretorius:
Causal Multi-Agent Reinforcement Learning: Review and Open Problems. CoRR abs/2111.06721 (2021) - 2020
- [j2]Arnu Pretorius, Herman Kamper, Steve Kroon:
On the expected behaviour of noise regularised deep neural networks as Gaussian processes. Pattern Recognit. Lett. 138: 75-81 (2020) - [j1]Arnu Pretorius, Elan Van Biljon, Benjamin van Niekerk, Ryan Eloff, Matthew Reynard, Steven D. James, Benjamin Rosman, Herman Kamper, Steve Kroon:
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. Pattern Recognit. Lett. 138: 95-105 (2020) - [c5]Arnu Pretorius, Scott Alexander Cameron, Elan Van Biljon, Tom Makkink, Shahil Mawjee, Jeremy du Plessis, Jonathan P. Shock, Alexandre Laterre, Karim Beguir:
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning. NeurIPS 2020 - [i8]Elan Van Biljon, Arnu Pretorius, Julia Kreutzer:
On Optimal Transformer Depth for Low-Resource Language Translation. CoRR abs/2004.04418 (2020) - [i7]Arnu Pretorius, Scott Alexander Cameron, Elan Van Biljon, Tom Makkink, Shahil Mawjee, Jeremy du Plessis, Jonathan P. Shock, Alexandre Laterre, Karim Beguir:
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning. CoRR abs/2010.07777 (2020)
2010 – 2019
- 2019
- [c4]Ryan Eloff, André Nortje, Benjamin van Niekerk, Avashna Govender, Leanne Nortje, Arnu Pretorius, Elan Van Biljon, Ewald van der Westhuizen, Lisa van Staden, Herman Kamper:
Unsupervised Acoustic Unit Discovery for Speech Synthesis Using Discrete Latent-Variable Neural Networks. INTERSPEECH 2019: 1103-1107 - [i6]Ryan Eloff, André Nortje, Benjamin van Niekerk, Avashna Govender, Leanne Nortje, Arnu Pretorius, Elan Van Biljon, Ewald van der Westhuizen, Lisa van Staden, Herman Kamper:
Unsupervised acoustic unit discovery for speech synthesis using discrete latent-variable neural networks. CoRR abs/1904.07556 (2019) - [i5]Arnu Pretorius, Herman Kamper, Steve Kroon:
On the expected behaviour of noise regularised deep neural networks as Gaussian processes. CoRR abs/1910.05563 (2019) - [i4]Arnu Pretorius, Elan Van Biljon, Benjamin van Niekerk, Ryan Eloff, Matthew Reynard, Steven D. James, Benjamin Rosman, Herman Kamper, Steve Kroon:
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. CoRR abs/1910.05725 (2019) - [i3]Felix McGregor, Arnu Pretorius, Johan A. du Preez, Steve Kroon:
Stabilising priors for robust Bayesian deep learning. CoRR abs/1910.10386 (2019) - 2018
- [c3]Arnu Pretorius, Steve Kroon, Herman Kamper:
Learning Dynamics of Linear Denoising Autoencoders. ICML 2018: 4138-4147 - [c2]Arnu Pretorius, Elan Van Biljon, Steve Kroon, Herman Kamper:
Critical initialisation for deep signal propagation in noisy rectifier neural networks. NeurIPS 2018: 5722-5731 - [i2]Arnu Pretorius, Steve Kroon, Herman Kamper:
Learning Dynamics of Linear Denoising Autoencoders. CoRR abs/1806.05413 (2018) - [i1]Arnu Pretorius, Elan Van Biljon, Steve Kroon, Herman Kamper:
Critical initialisation for deep signal propagation in noisy rectifier neural networks. CoRR abs/1811.00293 (2018) - 2016
- [c1]Arnu Pretorius, Douglas A. Parry:
Human Decision Making and Artificial Intelligence: A Comparison in the Domain of Sports Prediction. SAICSIT 2016: 32:1-32:10
Coauthor Index
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