Arnu Pretorius
Arnu Pretorius
Research Scientist, InstaDeep Ltd
Verified email at - Homepage
Cited by
Cited by
Unsupervised acoustic unit discovery for speech synthesis using discrete latent-variable neural networks
R Eloff, A Nortje, B van Niekerk, A Govender, L Nortje, A Pretorius, ...
arXiv preprint arXiv:1904.07556, 2019
A meta-analysis of research in random forests for classification
A Pretorius, S Bierman, SJ Steel
2016 Pattern Recognition Association of South Africa and Robotics and …, 2016
Learning dynamics of linear denoising autoencoders
A Pretorius, S Kroon, H Kamper
International Conference on Machine Learning, 2018
On optimal transformer depth for low-resource language translation
E Van Biljon, A Pretorius, J Kreutzer
arXiv preprint arXiv:2004.04418, 2020
Human decision making and artificial intelligence: a comparison in the domain of sports prediction
A Pretorius, DA Parry
Proceedings of the Annual Conference of the South African Institute of …, 2016
Critical initialisation for deep signal propagation in noisy rectifier neural networks
A Pretorius, E Van Biljon, S Kroon, H Kamper
Advances in Neural Information Processing Systems, 5722-5731, 2018
Towards a standardised performance evaluation protocol for cooperative marl
R Gorsane, O Mahjoub, RJ de Kock, R Dubb, S Singh, A Pretorius
Advances in Neural Information Processing Systems 35, 5510-5521, 2022
Causal multi-agent reinforcement learning: Review and open problems
SJ Grimbly, J Shock, A Pretorius
arXiv preprint arXiv:2111.06721, 2021
Mava: A research framework for distributed multi-agent reinforcement learning
A Pretorius, K Tessera, AP Smit, C Formanek, SJ Grimbly, K Eloff, ...
arXiv preprint arXiv:2107.01460, 2021
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning
A Pretorius, S Cameron, E Van Biljon, T Makkink, S Mawjee, J du Plessis, ...
Advances in neural information processing systems 33, 9983-9994, 2020
On the expected behaviour of noise regularised deep neural networks as Gaussian processes
A Pretorius, H Kamper, S Kroon
Pattern Recognition Letters 138, 75-81, 2020
A bias-variance analysis of ensemble learning for classification
A Pretorius, S Bierman, SJ Steel
Annual Proceedings of the South African Statistical Association Conference …, 2016
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
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks
A Pretorius, E Van Biljon, B van Niekerk, R Eloff, M Reynard, S James, ...
Pattern Recognition Letters 138, 95-105, 2020
Stabilising priors for robust bayesian deep learning
F McGregor, A Pretorius, J Preez, S Kroon
arXiv preprint arXiv:1910.10386, 2019
Advances in random forests with application to classification
A Pretorius
Stellenbosch: Stellenbosch University, 2016
Off-the-Grid MARL: a Framework for Dataset Generation with Baselines for Cooperative Offline Multi-Agent Reinforcement Learning
C Formanek, A Jeewa, J Shock, A Pretorius
arXiv preprint arXiv:2302.00521, 2023
Universally expressive communication in multi-agent reinforcement learning
M Morris, TD Barrett, A Pretorius
Advances in Neural Information Processing Systems 35, 33508-33522, 2022
On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa
IS Yusuf, K Tessera, T Tumiel, Z Slim, A Kerkeni, S Nevo, A Pretorius
arXiv preprint arXiv:2111.03904, 2021
Learning to communicate through imagination with model-based deep multi-agent reinforcement learning
A Pretorius, S Cameron, AP Smit, E van Biljon, L Francis, F Azeez, ...
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