Publications and Output

  • Gupta, Ankush and Vedaldi, Andrea and Zisserman, Andrew.  Synthetic Data for Text Localisation in Natural Images The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) June 2016
  • Ghoshal, Sid and S. Roberts, Extracting Predictive Information from Heterogeneous Data Streams using Gaussian Processes, Algorithmic Finance, vol. 5, no. 1-2, pp. 21-30, 2016.
  • Leonard Hasenclever, Stefan Webb, Thibaut Lienart, Sebastian Vollmer, Balaji Lakshminarayanan, Charles Blundell, Yee Whye Teh, Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server. http://arxiv.org/abs/1512.09327 (Under review)
  • Learning Grimaces by Watching TV”  – Sam Albanie and Andrea Vedaldi, accepted into BMVC 2016.
  • “James Thewlis, Shuai Zheng, Philip H. S. Torr, Andrea Vedaldi.  Fully-Trainable Deep Matching. British  Machine Vision Conference (BMVC), 2016.
  • Bartlett, O, C. Gurau, L. Marchegiani, and I. Posner, “Enabling Intelligent Energy Management for Robots using Publicly Available Maps,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016. PDF
  • Berrada, Leo, Trusting SVM for Piecewise Linear CNNs” has been accepted at ICLR 2017 (International Conference on Learning Representations). It is available on arXiv at https://arxiv.org/abs/1611.02185
  • Ghoshal, S and Roberts, S. Reading the Tea Leaves: A Neural Network Perspective on Technical Trading. Knowledge Discovery and Data Mining (KDD), 2017.
  • Cobb, A and Markham, A and Roberts, S. Learning from lions: inferring the utility of agents from their trajectories. Available at https://arxiv.org/pdf/1709.02357.pdf
  • Jakob Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos, Philip H.S. Torr, Pushmeet Kohli, Shimon Whiteson, Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning.   Accepted at ICML2017. Available at https://arxiv.org/abs/1702.08887
  • Unsupervised object learning from dense invariant image labelling, J.Thewlis and H. Bilen and A. Vedaldi, Proceedings of Advances in Neural Information Processing Systems (NIPS), 2017 (oral presentation)
  • Unsupervised learning of object landmarks by factorized spatial embeddings, J. Thewlis and H. Bilen and A. Vedaldi, Proceedings of the International Conference on Computer Vision (ICCV), 2017 (oralpresentation)