Arnu Pretorius

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 44

Top Topics

Reinforcement Learning

Theoretic Analysis

Gaussian Processes

Top Venues

Pattern Recognit. Lett.

Publications

Ulrich A. Mbou Sob, Qiulin Li, Miguel Arbesú, Oliver Bent, Andries P. Smit, Arnu Pretorius
Generative Model for Small Molecules with Latent Space RL Fine-Tuning to Protein Targets. CoRR (2024)
Callum Rhys Tilbury, Claude Formanek, Louise Beyers, Jonathan P. Shock, Arnu Pretorius
Coordination Failure in Cooperative Offline MARL. CoRR (2024)
Ibrahim Salihu Yusuf, Mukhtar Opeyemi Yusuf, Kobby Panford-Quainoo, Arnu Pretorius
A Geospatial Approach to Predicting Desert Locust Breeding Grounds in Africa. CoRR (2024)
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, Andries P. Smit, Nathan Grinsztajn, Raphaël Boige, Cemlyn N. Waters, Mohamed A. Mimouni, Ulrich A. Mbou Sob, Ruan de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre
Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX. ICLR (2024)
Claude Formanek, Callum Rhys Tilbury, Louise Beyers, Jonathan P. Shock, Arnu Pretorius
Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation. CoRR (2024)
Félix Chalumeau, Refiloe Shabe, Noah de Nicola, Arnu Pretorius, Thomas D. Barrett, Nathan Grinsztajn
Memory-Enhanced Neural Solvers for Efficient Adaptation in Combinatorial Optimization. CoRR (2024)
Félix Chalumeau, Shikha Surana, Clément Bonnet, Nathan Grinsztajn, Arnu Pretorius, Alexandre Laterre, Tom Barrett
Combinatorial Optimization with Policy Adaptation using Latent Space Search. NeurIPS (2023)
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) (2023)
Claude Formanek, Callum Rhys Tilbury, Jonathan P. Shock, Kale-ab Tessera, Arnu Pretorius
Reduce, Reuse, Recycle: Selective Reincarnation in Multi-Agent Reinforcement Learning. CoRR (2023)
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, Ulrich A. Mbou Sob, Omayma Mahjoub, Elshadai Tegegn, Mohamed A. Mimouni, Raphaël Boige, Ruan de Kock, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre
Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX. CoRR (2023)
Félix Chalumeau, Shikha Surana, Clément Bonnet, Nathan Grinsztajn, Arnu Pretorius, Alexandre Laterre, Thomas D. Barrett
Combinatorial Optimization with Policy Adaptation using Latent Space Search. CoRR (2023)
Wiem Khlifi, Siddarth Singh, Omayma Mahjoub, Ruan de Kock, Abidine Vall, Rihab Gorsane, Arnu Pretorius
On Diagnostics for Understanding Agent Training Behaviour in Cooperative MARL. CoRR (2023)
Scott Alexander Cameron, Arnu Pretorius, Stephen J. Roberts
Nonparametric Boundary Geometry in Physics Informed Deep Learning. NeurIPS (2023)
Andries P. Smit, Paul Duckworth, Nathan Grinsztajn, Kale-ab Tessera, Thomas D. Barrett, Arnu Pretorius
Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A. CoRR (2023)
Siddarth Singh, Omayma Mahjoub, Ruan de Kock, Wiem Khlifi, Abidine Vall, Kale-ab Tessera, Arnu Pretorius
How much can change in a year? Revisiting Evaluation in Multi-Agent Reinforcement Learning. CoRR (2023)
Claude Formanek, Asad Jeewa, Jonathan P. Shock, Arnu Pretorius
Off-the-Grid MARL: Datasets and Baselines for Offline Multi-Agent Reinforcement Learning. AAMAS (2023)
Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius
Generalisable Agents for Neural Network Optimisation. CoRR (2023)
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 (2023)
Omayma Mahjoub, Ruan de Kock, Siddarth Singh, Wiem Khlifi, Abidine Vall, Kale-ab Tessera, Arnu Pretorius
Efficiently Quantifying Individual Agent Importance in Cooperative MARL. CoRR (2023)
Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL. CoRR (2022)
Matthew Morris, Thomas D. Barrett, Arnu Pretorius
Universally Expressive Communication in Multi-Agent Reinforcement Learning. CoRR (2022)
Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts
Robust and Scalable SDE Learning: A Functional Perspective. ICLR (2022)
Matthew Morris, Thomas D. Barrett, Arnu Pretorius
Universally Expressive Communication in Multi-Agent Reinforcement Learning. NeurIPS (2022)
Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL. NeurIPS (2022)
Arnu Pretorius, Kale-ab Tessera, Andries P. Smit, Claude Formanek, St John Grimbly, Kevin Eloff, Siphelele Danisa, Lawrence Francis, Jonathan Shock, Herman Kamper, Willie Brink, Herman A. Engelbrecht, Alexandre Laterre, Karim Beguir
Mava: a research framework for distributed multi-agent reinforcement learning. CoRR (2021)
St John Grimbly, Jonathan Shock, Arnu Pretorius
Causal Multi-Agent Reinforcement Learning: Review and Open Problems. CoRR (2021)
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 (2021)
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 (2021)
Scott Cameron, Tyron Cameron, Arnu Pretorius, Stephen Roberts
Robust and Scalable SDE Learning: A Functional Perspective. CoRR (2021)
Arnu Pretorius, Herman Kamper, Steve Kroon
On the expected behaviour of noise regularised deep neural networks as Gaussian processes. Pattern Recognit. Lett. 138 (2020)
Elan Van Biljon, Arnu Pretorius, Julia Kreutzer
On Optimal Transformer Depth for Low-Resource Language Translation. CoRR (2020)
Arnu Pretorius, Scott Cameron, Elan Van Biljon, Tom Makkink, Shahil Mawjee, Jeremy du Plessis, Jonathan 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)
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 (2020)
Arnu Pretorius, Scott Cameron, Elan Van Biljon, Tom Makkink, Shahil Mawjee, Jeremy du Plessis, Jonathan Shock, Alexandre Laterre, Karim Beguir
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning. CoRR (2020)
Felix McGregor, Arnu Pretorius, Johan A. du Preez, Steve Kroon
Stabilising priors for robust Bayesian deep learning. CoRR (2019)
Arnu Pretorius, Herman Kamper, Steve Kroon
On the expected behaviour of noise regularised deep neural networks as Gaussian processes. CoRR (2019)
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 (2019)
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)
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 (2019)
Arnu Pretorius, Elan Van Biljon, Steve Kroon, Herman Kamper
Critical initialisation for deep signal propagation in noisy rectifier neural networks. CoRR (2018)
Arnu Pretorius, Elan Van Biljon, Steve Kroon, Herman Kamper
Critical initialisation for deep signal propagation in noisy rectifier neural networks. NeurIPS (2018)
Arnu Pretorius, Steve Kroon, Herman Kamper
Learning Dynamics of Linear Denoising Autoencoders. CoRR (2018)
Arnu Pretorius, Steve Kroon, Herman Kamper
Learning Dynamics of Linear Denoising Autoencoders. ICML (2018)
Arnu Pretorius, Douglas A. Parry
Human Decision Making and Artificial Intelligence: A Comparison in the Domain of Sports Prediction. SAICSIT (2016)