Scaling Instructable Agents Across Many Simulated Worlds; Abi Raad, Ahuja, Barros, Besse, Bolt, Bolton, Brownfield, Buttimore, Cant, Chakera, et al.; arXiv preprint arXiv:2404.10179; 2024.
VAE-Loco: Versatile Quadruped Locomotion by Learning a Disentangled Gait Representation; Mitchell, Merkt, Geisert, Gangapurwala, Engelcke, Parker Jones, Havoutis, Posner; IEEE Transactions on Robotics (T-RO); 2023.
Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulation; Hung, Zhong, Goodwin, Parker Jones, Engelcke, Havoutis, Posner; IEEE Robotics and Automation Letters (RA-L); 2022.
Next Steps: Learning a Disentangled Gait Representation for Versatile Quadruped Locomotion; Mitchell, Merkt, Geisert, Gangapurwala, Engelcke, Parker Jones, Havoutis, Posner; IEEE International Conference on Robotics and Automation (ICRA); 2022.
Universal Approximation of Functions on Sets; Wagstaff, Fuchs, Engelcke, Osborne, Posner; Journal of Machine Learning Research (JMLR); 2022.
APEX: Unsupervised, Object-Centric Scene Segmentation and Tracking for Robot Manipulation; Wu, Parker Jones, Engelcke, Posner; IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 2021.
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement; Engelcke, Parker Jones, Posner; Advances in Neural Information Processing Systems (NeurIPS); 2021.
Reconstruction Bottlenecks in Object-Centric Generative Models; Engelcke, Parker Jones, Posner; Workshop on Object-Oriented Learning at ICML 2020; 2020.
First Steps: Latent-Space Control with Semantic Constraints for Quadruped Locomotion; Mitchell, Engelcke, Parker Jones, Surovik, Gangapurwala, Melon, Havoutis, Posner; IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 2020.
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces; Ehrhardt, Groth, Monszpart, Engelcke, Posner, Mitra, Vedaldi; Advances in Neural Information Processing Systems (NeurIPS); 2020.
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations; Engelcke, Kosiorek, Parker Jones, Posner; International Conference on Learning Representations (ICLR); 2020.
On the Limitations of Representing Functions on Sets; Wagstaff, Fuchs, Engelcke, Posner, Osborne; International Conference on Machine Learning (ICML); 2019.
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks; Graham, Engelcke, van der Maaten; IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 2018.
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55; Yi, Shao, Savva, Huang, Zhou, Wang, Graham, Engelcke, Klokov, Lempitsky, et al.; arXiv preprint arXiv:1710.06104; 2017.
Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks; Engelcke, Rao, Wang, Tong, Posner; IEEE International Conference on Robotics and Automation (ICRA); 2017.
