Alexander I. Cowen-Rivers

22 papers A* 2Misc 1Journal 16Unranked 3

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation. CoRR Mohammad Asif Khan, Alexander I. Cowen-Rivers, Derrick-Goh-Xin Deik, Antoine Grosnit, Kamil Dreczkowski, Philippe A. Robert, Victor Greiff, Rasul Tutunov, Dany Bou-Ammar, Jun Wang, Haitham Bou-Ammar
2022	A*	`conf`	Enhancing Safe Exploration Using Safety State Augmentation. NeurIPS Aivar Sootla, Alexander I. Cowen-Rivers, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	Enhancing Safe Exploration Using Safety State Augmentation. CoRR Aivar Sootla, Alexander I. Cowen-Rivers, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. J. Artif. Intell. Res. Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov, Zhi Wang, Antoine Grosnit, Ryan-Rhys Griffiths, Alexandre Max Maraval, Jianye Hao, Jun Wang, Jan Peters, Haitham Bou-Ammar
2022	J	`jnl`	SAMBA: safe model-based & active reinforcement learning. Mach. Learn. Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	SAUTE RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. CoRR Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Mguni, Jun Wang, Haitham Bou-Ammar
2022	A*	`conf`	Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. ICML Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Henry Mguni, Jun Wang, Haitham Ammar
2022	J	`jnl`	Structured Q-learning For Antibody Design. CoRR Alexander I. Cowen-Rivers, Philip John Gorinski, Aivar Sootla, Asif Khan, Furui Liu, Jun Wang, Jan Peters, Haitham Bou-Ammar
2021	J	`jnl`	Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? J. Mach. Learn. Res. Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
2021	J	`jnl`	High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. CoRR Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander I. Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar
2020	J	`jnl`	Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? CoRR Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
2020	J	`jnl`	Emergent Communication with World Models. CoRR Alexander I. Cowen-Rivers, Jason Naradowsky
2020	J	`jnl`	HEBO: Heteroscedastic Evolutionary Bayesian Optimisation. CoRR Alexander I. Cowen-Rivers, Wenlong Lyu, Zhi Wang, Rasul Tutunov, Jianye Hao, Jun Wang, Haitham Bou-Ammar
2020	J	`jnl`	SAMBA: Safe Model-Based & Active Reinforcement Learning. CoRR Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Ammar
2020	Misc	`conf`	SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. CoRL Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Zhengbang Zhu, Yihan Ni, Nhat M. Nguyen, Mohamed Elsayed, Haitham Ammar, Alexander I. Cowen-Rivers, Sanjeevan Ahilan, Zheng Tian, Daniel Palenicek, Kasra Rezaee, Peyman Yadmellat, Kun Shao, Dong Chen, Baokuan Zhang, Hongbo Zhang, Jianye Hao, Wulong Liu, Jun Wang
2020	J	`jnl`	SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. CoRR Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat M. Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander I. Cowen-Rivers, Zheng Tian, Daniel Palenicek, Haitham Bou-Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang
2019	J	`jnl`	Infer Your Enemies and Know Yourself, Learning in Real-Time Bidding with Partially Observable Opponents. CoRR Manxing Du, Alexander I. Cowen-Rivers, Ying Wen, Phu Sakulwongtana, Jun Wang, Mats Brorsson, Radu State
2019	—	`conf`	Know Your Enemies and Know Yourself in the Real-Time Bidding Function Optimisation. ICDM Workshops Manxing Du, Alexander I. Cowen-Rivers, Ying Wen, Phu Sakulwongtana, Jun Wang, Mats Brorsson, Radu State
2019	—	`conf`	Neural Variational Inference For Estimating Knowledge Graph Embedding Uncertainty. NeSy@IJCAI Alexander I. Cowen-Rivers, Pasquale Minervini, Sebastian Riedel, Tim Rocktäschel, Jun Wang, Matko Bosnjak
2019	J	`jnl`	Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings. CoRR Alexander I. Cowen-Rivers, Pasquale Minervini, Tim Rocktäschel, Matko Bosnjak, Sebastian Riedel, Jun Wang
2019	J	`jnl`	RL: Generic reinforcement learning codebase in TensorFlow. J. Open Source Softw. Bryan M. Li, Alexander I. Cowen-Rivers, Piotr Kozakowski, David Tao, Siddhartha Kamalakara, Nitarshan Rajkumar, Hariharan Sezhiyan, Sicong Huang, Aidan N. Gomez
2018	—	`conf`	Towards Incremental Cylindrical Algebraic Decomposition in Maple. SC-Square@FLOC Alexander I. Cowen-Rivers, Matthew England