Ten papers with MLG authors to appear at ICML 2017

Ten papers including authors from the Cambridge Machine Learning Group will appear at the International Conference for Machine Learning (ICML) 2017. They are:

Li Y. and Gal Y.

Dropout inference in Bayesian neural networks with alpha-divergences.

Hernández-Lobato J. M., Requeima J., Pyzer-Knapp E. O. and Aspuru-Guzik A.

Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space.

Kusner M. J., Paige B. and Hernández-Lobato J. M.

Grammar Variational Autoencoder.

Jaques N., Gu S., Bahdanau S., Hernndez Lobato J. M., Turner R. E. and Eck D.

Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control.

Balog, M., Tripuraneni, N., Ghahramani, Z. and Weller, A.

Lost Relatives of the Gumbel Trick.

Tripuraneni, N., Rowland, M. Ghahramani, Z., and Turner, R. E.

Magnetic Hamiltonian Monte Carlo.

Valera, I. and Ghahramani, Z.

Automatic Discovery of the Statistical Types of Variables in a Dataset.

Lee, J., Heaukulani, C., James, L., Choi, S. and Ghahramani, Z.

Bayesian inference on random simple graphs with power law degree distributions.

Palla, K., Knowles, D.A., and Ghahramani, Z.

A birth-death process for feature allocation.

Gal, Y., Islam, R. and Ghahramani, Z.

Deep Bayesian Active Learning with Image Data.