Human Decision Making and Artificial Intelligence: A Comparison in the Domain of Sports Prediction. - Arnu Pretorius; Douglas A. Parry (SAICSIT, 2016)

Learning Dynamics of Linear Denoising Autoencoders. - Arnu Pretorius; Steve Kroon; Herman Kamper (ICML, 2018)

Critical initialisation for deep signal propagation in noisy rectifier neural networks. - Arnu Pretorius; Elan Van Biljon; Steve Kroon; Herman Kamper (NeurIPS, 2018)

Unsupervised Acoustic Unit Discovery for Speech Synthesis Using Discrete Latent-Variable Neural Networks. - 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 (INTERSPEECH, 2019)

Stabilising priors for robust Bayesian deep learning. - Felix McGregor; Arnu Pretorius; Johan A. du Preez; Steve Kroon (CoRR, 2019)

A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning. - Arnu Pretorius; Scott Alexander Cameron; Elan Van Biljon; Tom Makkink; Shahil Mawjee; Jeremy du Plessis; Jonathan P. Shock; Alexandre Laterre; Karim Beguir (NeurIPS, 2020)

On Optimal Transformer Depth for Low-Resource Language Translation. - Elan Van Biljon; Arnu Pretorius; Julia Kreutzer (AfricaNLP, 2020)

If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. - Arnu Pretorius; Elan Van Biljon; Benjamin van Niekerk; Ryan Eloff; Matthew Reynard; Steven James 001; Benjamin Rosman; Herman Kamper; Steve Kroon (Pattern Recognit. Lett., 2020)

On the expected behaviour of noise regularised deep neural networks as Gaussian processes. - Arnu Pretorius; Herman Kamper; Steve Kroon (Pattern Recognit. Lett., 2020)

Mava: a research framework for distributed multi-agent reinforcement learning. - Arnu Pretorius; Kale-ab Abebe 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; et al. (CoRR, 2021)

Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel. - Kevin Eloff; Arnu Pretorius; Okko Räsänen; Herman A. Engelbrecht; Herman Kamper (CoRR, 2021)

On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa. - Ibrahim Salihu Yusuf; Kale-ab Abebe Tessera; Thomas Tumiel; Sella Nevo; Arnu Pretorius (CoRR, 2021)

Causal Multi-Agent Reinforcement Learning: Review and Open Problems. - St John Grimbly; Jonathan P. Shock; Arnu Pretorius (CoRR, 2021)

Robust and Scalable SDE Learning: A Functional Perspective. - Scott Alexander Cameron; Tyron Luke Cameron; Arnu Pretorius; Stephen J. Roberts (ICLR, 2022)

Towards a Standardised Performance Evaluation Protocol for Cooperative MARL. - Rihab Gorsane; Omayma Mahjoub; Ruan de Kock; Roland Dubb; Siddarth Singh; Arnu Pretorius (NeurIPS, 2022)

Universally Expressive Communication in Multi-Agent Reinforcement Learning. - Matthew Morris; Thomas D. Barrett; Arnu Pretorius (NeurIPS, 2022)

Off-the-Grid MARL: Datasets and Baselines for Offline Multi-Agent Reinforcement Learning. - Claude Formanek; Asad Jeewa; Jonathan P. Shock; Arnu Pretorius (AAMAS, 2023)

Nonparametric Boundary Geometry in Physics Informed Deep Learning. - Scott Alexander Cameron; Arnu Pretorius; Stephen J. Roberts (NeurIPS, 2023)

Combinatorial Optimization with Policy Adaptation using Latent Space Search. - Félix Chalumeau; Shikha Surana; Clément Bonnet; Nathan Grinsztajn; Arnu Pretorius; Alexandre Laterre; Tom Barrett (NeurIPS, 2023)

Off-the-Grid MARL: a Framework for Dataset Generation with Baselines for Cooperative Offline Multi-Agent Reinforcement Learning. - Claude Formanek; Asad Jeewa; Jonathan P. Shock; Arnu Pretorius (CoRR, 2023)

Reduce, Reuse, Recycle: Selective Reincarnation in Multi-Agent Reinforcement Learning. - Claude Formanek; Callum Rhys Tilbury; Jonathan P. Shock; Kale-ab Abebe Tessera; Arnu Pretorius (CoRR, 2023)

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX. - Clément Bonnet; Daniel Luo; Donal Byrne; Shikha Surana; Vincent Coyette; Paul Duckworth; Laurence I. Midgley; Tristan Kalloniatis; Sasha Abramowitz; Cemlyn N. Waters; Andries P. Smit; Nathan Grinsztajn; et al. (CoRR, 2023)

Combinatorial Optimization with Policy Adaptation using Latent Space Search. - Félix Chalumeau; Shikha Surana; Clément Bonnet; Nathan Grinsztajn; Arnu Pretorius; Alexandre Laterre; Thomas D. Barrett (CoRR, 2023)

Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A. - Andries P. Smit; Paul Duckworth; Nathan Grinsztajn; Kale-ab Abebe Tessera; Thomas D. Barrett; Arnu Pretorius (CoRR, 2023)

Generalisable Agents for Neural Network Optimisation. - Kale-ab Abebe Tessera; Callum Rhys Tilbury; Sasha Abramowitz; Ruan de Kock; Omayma Mahjoub; Benjamin Rosman; Sara Hooker; Arnu Pretorius (CoRR, 2023)

How much can change in a year? Revisiting Evaluation in Multi-Agent Reinforcement Learning. - Siddarth Singh; Omayma Mahjoub; Ruan de Kock; Wiem Khlifi; Abidine Vall; Kale-ab Abebe Tessera; Arnu Pretorius (CoRR, 2023)

Efficiently Quantifying Individual Agent Importance in Cooperative MARL. - Omayma Mahjoub; Ruan de Kock; Siddarth Singh; Wiem Khlifi; Abidine Vall; Kale-ab Abebe Tessera; Arnu Pretorius (CoRR, 2023)

On Diagnostics for Understanding Agent Training Behaviour in Cooperative MARL. - Wiem Khlifi; Siddarth Singh; Omayma Mahjoub; Ruan de Kock; Abidine Vall; Rihab Gorsane; Arnu Pretorius (CoRR, 2023)

Scaling multi-agent reinforcement learning to full 11 versus 11 simulated robotic football. - Andries P. Smit; Herman A. Engelbrecht; Willie Brink; Arnu Pretorius (Auton. Agents Multi Agent Syst., 2023)

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX. - Clément Bonnet; Daniel Luo; Donal Byrne; Shikha Surana; Sasha Abramowitz; Paul Duckworth; Vincent Coyette; Laurence Illing Midgley; Elshadai Tegegn; Tristan Kalloniatis; Omayma Mahjoub; Matthew Macfarlane; et al. (ICLR, 2024)

Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs. - Andries P. Smit; Nathan Grinsztajn; Paul Duckworth; Thomas D. Barrett; Arnu Pretorius (ICML, 2024)

Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation. - Juan Claude Formanek; Callum Rhys Tilbury; Louise Beyers; Jonathan P. Shock; Arnu Pretorius (NeurIPS, 2024)

A Geospatial Approach to Predicting Desert Locust Breeding Grounds in Africa. - Ibrahim Salihu Yusuf; Mukhtar Opeyemi Yusuf; Kobby Panford-Quainoo; Arnu Pretorius (CoRR, 2024)

Memory-Enhanced Neural Solvers for Efficient Adaptation in Combinatorial Optimization. - Félix Chalumeau; Refiloe Shabe; Noah de Nicola; Arnu Pretorius; Thomas D. Barrett; Nathan Grinsztajn (CoRR, 2024)

Coordination Failure in Cooperative Offline MARL. - Callum Rhys Tilbury; Claude Formanek; Louise Beyers; Jonathan P. Shock; Arnu Pretorius (CoRR, 2024)

Generative Model for Small Molecules with Latent Space RL Fine-Tuning to Protein Targets. - Ulrich A. Mbou Sob; Qiulin Li; Miguel Arbesú; Oliver Bent; Andries P. Smit; Arnu Pretorius (CoRR, 2024)

Putting Data at the Centre of Offline Multi-Agent Reinforcement Learning. - Claude Formanek; Louise Beyers; Callum Rhys Tilbury; Jonathan P. Shock; Arnu Pretorius (CoRR, 2024)

Performant, Memory Efficient and Scalable Multi-Agent Reinforcement Learning. - Omayma Mahjoub; Sasha Abramowitz; Ruan de Kock; Wiem Khlifi; Simon du Toit; Jemma Daniel; Louay Ben Nessir; Louise Beyers; Claude Formanek; Liam Clark; Arnu Pretorius (CoRR, 2024)

Multi-Agent Reinforcement Learning with Selective State-Space Models. - Jemma Daniel; Ruan John de Kock; Louay Ben Nessir; Sasha Abramowitz; Omayma Mahjoub; Wiem Khlifi; Juan Claude Formanek; Arnu Pretorius (AAMAS, 2025)

Is an Exponentially Growing Action Space Really that Bad? Validating a Core Assumption for using Multi-Agent RL. - Ruan de Kock; Arnu Pretorius; Jonathan P. Shock (AAMAS, 2025)

Breaking the Performance Ceiling in Complex Reinforcement Learning requires Inference Strategies. - Félix Chalumeau; Daniel Rajaonarivonivelomanantsoa; Ruan de Kock; Claude Formanek; Sasha Abramowitz; Omayma Mahjoub; Wiem Khlifi; Simon du Toit; Louay Ben Nessir; Refiloe Shabe; Arnol Fokam; Siddarth Singh; et al. (CoRR, 2025)

Oryx: a Performant and Scalable Algorithm for Many-Agent Coordination in Offline MARL. - Claude Formanek; Omayma Mahjoub; Louay Ben Nessir; Sasha Abramowitz; Ruan de Kock; Wiem Khlifi; Simon du Toit; Félix Chalumeau; Daniel Rajaonarivonivelomanantsoa; Arnol Fokam; Siddarth Singh; Ulrich A. Mbou Sob; et al. (CoRR, 2025)