These pages contain selected publications which serve as examples of the contributions by the researchers at Oxford and the ATI.

Publications by Oxford researchers funded by the Alan Turing Institute are included.

Neural Programmer−Interpreters

Date: 2016

Categories:

Reference

Reed, S. and Freitas, N. (2016) ‘Neural Programmer−Interpreters’, International Conference on Learning Representations (ICLR).

Full text available at arxiv.org

Author

Prof. Nando de Freitas

P-values: Misunderstood and misused

Date: 2016

Categories:

Reference

Vidgen, B. and Yasseri, T. (2016) ‘P-values: Misunderstood and misused’, Frontiers in Physics, 4(6). doi: 10.3389/fphy.2016.00006.

Full text available at arxiv.org

Author

Dr. Taha Yasseri

Learning to communicate to solve riddles with deep distributed recurrent Q-Networks

Date: 2016

Categories:

Reference

Foerster, J.N., Assael, Y.M., Freitas, N. and Whiteson, S. (2016) ‘Learning to communicate to solve riddles with deep distributed recurrent Q-Networks’.

Full text available at arxiv.org

Author

Prof. Nando de Freitas

The net as a knowledge machine: How the Internet became embedded in research

Date: 2016

Categories:

Reference

Meyer, E.T., Schroeder, R. and Cowls, J. (2016) ‘The net as a knowledge machine: How the Internet became embedded in research’, New Media & Society, . doi: 10.1177/1461444816643793.

Full text available at nms.sagepub.com

Author

Prof. Eric T. Meyer

Distance in the Forest Fire model how far are you from eve?

Date: 2016

Categories:

Reference

Kanade, V., Levi, R., Lotker, Z., Mallmann-Trenn, F. and Mathieu, C. (2016) ‘Distance in the Forest Fire model how far are you from eve?’, 27th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2016).

Full text available at www.cs.ox.ac.uk

Author

Dr. Varun Kanade

Preferential query answering in the semantic web with Possibilistic networks

Date: 2016

Categories:

Reference

Borgwardt, S., Fazzinga, B., Lukasiewicz, T., Shrivastava, A. and Tifrea-Marciuska, O. (2016) ‘Preferential query answering in the semantic web with Possibilistic networks’, 25th International Joint Conference on Artificial Intelligence‚ IJCAI 2016.

Full text available at lat.inf.tu-dresden.de

Author

Prof. Thomas Lukasiewicz

Consistency and fluctuations for stochastic gradient Langevin dynamics

Date: 2016

Categories:

Reference

Teh, Y.W., Thiery, A.H. and Vollmer, S.J. (2016) ‘Consistency and fluctuations for stochastic gradient Langevin dynamics’, Journal of Machine Learning Research, 17, pp. 1–33.

Full text available at www.jmlr.org

Author

Prof. Yee Whye Teh

Bayesian Learning of Kernel Embeddings

Date: 2016

Categories:

Reference

S. Flaxman, D. Sejdinovic, J. P. Cunningham, and S. Filippi, Bayesian Learning of Kernel Embeddings, in Uncertainty in Artificial Intelligence (UAI), 2016.

Full text available at www.auai.org

Authors

Prof. Dino Sejdinovic
Dr. Sarah Filippi

Global and local information in clustering labelled block models

Date: 2016

Categories:

Reference

Kanade, V., Mossel, E. and Schramm, T. (2016) ‘Global and local information in clustering labelled block models’, 18th International Workshop on Randomization and Computation (RANDOM 2014), . doi: 10.1109/TIT.2016.2516564.

No publisher link available

Author

Dr. Varun Kanade