Towards Incremental Cylindrical Algebraic Decomposition in Maple. - Alexander I. Cowen-Rivers; Matthew England 001 (SC-Square@FLOC, 2018)

Summer Research Report: Towards Incremental Lazard Cylindrical Algebraic Decomposition. - Alexander Imani Cowen-Rivers; Matthew England 001 (CoRR, 2018)

Know Your Enemies and Know Yourself in the Real-Time Bidding Function Optimisation. - Manxing Du; Alexander I. Cowen-Rivers; Ying Wen 001; Phu Sakulwongtana; Jun Wang 012; Mats Brorsson; Radu State (ICDM Workshops, 2019)

Neural Variational Inference For Estimating Knowledge Graph Embedding Uncertainty. - Alexander I. Cowen-Rivers; Pasquale Minervini; Sebastian Riedel 001; Tim Rocktäschel; Jun Wang 012; Matko Bosnjak (NeSy@IJCAI, 2019)

Infer Your Enemies and Know Yourself, Learning in Real-Time Bidding with Partially Observable Opponents. - Manxing Du; Alexander I. Cowen-Rivers; Ying Wen 001; Phu Sakulwongtana; Jun Wang 012; Mats Brorsson; Radu State (CoRR, 2019)

Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings. - Alexander I. Cowen-Rivers; Pasquale Minervini; Tim Rocktäschel; Matko Bosnjak; Sebastian Riedel 001; Jun Wang 012 (CoRR, 2019)

RL: Generic reinforcement learning codebase in TensorFlow. - Bryan M. Li; Alexander I. Cowen-Rivers; Piotr Kozakowski; David Tao; Siddhartha Kamalakara; Nitarshan Rajkumar; Hariharan Sezhiyan; Sicong Huang 001; Aidan N. Gomez (J. Open Source Softw., 2019)

SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. - Ming Zhou 006; Jun Luo 009; Julian Villela; Yaodong Yang 002; David Rusu; Jiayu Miao; Weinan Zhang 001; Montgomery Alban; Iman Fadakar; Zheng Chen; Chongxi Huang; Ying Wen 001; et al. (CoRL, 2020)

Emergent Communication with World Models. - Alexander I. Cowen-Rivers; Jason Naradowsky (CoRR, 2020)

SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. - Ming Zhou 006; Jun Luo 009; Julian Villela; Yaodong Yang 002; David Rusu; Jiayu Miao; Weinan Zhang 001; Montgomery Alban; Iman Fadakar; Zheng Chen; Aurora Chongxi Huang; Ying Wen 001; et al. (CoRR, 2020)

HEBO: Heteroscedastic Evolutionary Bayesian Optimisation. - Alexander I. Cowen-Rivers; Wenlong Lyu; Zhi Wang 001; Rasul Tutunov; Jianye Hao; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2020)

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. - Antoine Grosnit; Rasul Tutunov; Alexandre Max Maraval; Ryan-Rhys Griffiths; Alexander I. Cowen-Rivers; Lin Yang; Lin Zhu; Wenlong Lyu; Zhitang Chen; Jun Wang 012; Jan Peters 001; Haitham Bou-Ammar (CoRR, 2021)

Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? - Antoine Grosnit; Alexander I. Cowen-Rivers; Rasul Tutunov; Ryan-Rhys Griffiths; Jun Wang 012; Haitham Bou-Ammar (J. Mach. Learn. Res., 2021)

Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. - Aivar Sootla; Alexander I. Cowen-Rivers; Taher Jafferjee; Ziyan Wang; David Henry Mguni; Jun Wang 012; Haitham Ammar (ICML, 2022)

Enhancing Safe Exploration Using Safety State Augmentation. - Aivar Sootla; Alexander I. Cowen-Rivers; Jun Wang 012; Haitham Bou-Ammar (NeurIPS, 2022)

Learning Geometric Constraints in Task and Motion Planning. - Tianyu Ren; Alexander Imani Cowen-Rivers; Haitham Bou-Ammar; Jan Peters 001 (CoRR, 2022)

AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation. - Mohammad Asif Khan 001; Alexander I. Cowen-Rivers; Derrick-Goh-Xin Deik; Antoine Grosnit; Kamil Dreczkowski; Philippe A. Robert; Victor Greiff; Rasul Tutunov; Dany Bou-Ammar; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2022)

Structured Q-learning For Antibody Design. - Alexander I. Cowen-Rivers; Philip John Gorinski; Aivar Sootla; Asif Khan 008; Furui Liu; Jun Wang 012; Jan Peters 001; Haitham Bou-Ammar (CoRR, 2022)

HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. - Alexander I. Cowen-Rivers; Wenlong Lyu; Rasul Tutunov; Zhi Wang 001; Antoine Grosnit; Ryan-Rhys Griffiths; Alexandre Max Maraval; Jianye Hao; Jun Wang 012; Jan Peters 001; Haitham Bou-Ammar (J. Artif. Intell. Res., 2022)

SAMBA: safe model-based & active reinforcement learning. - Alexander I. Cowen-Rivers; Daniel Palenicek; Vincent Moens; Mohammed Amin Abdullah 001; Aivar Sootla; Jun Wang 012; Haitham Bou-Ammar (Mach. Learn., 2022)

Pushing The Limits of Sample-Efficient Optimisation. - Alexander Imani Cowen-Rivers (2023)