# Shakir Mohamed

According to our database

Collaborative distances:

^{1}, Shakir Mohamed authored at least 22 papers between 2006 and 2018.Collaborative distances:

## Timeline

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Book In proceedings Article PhD thesis Other## Links

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## Bibliography

2018

Implicit Reparameterization Gradients.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Implicit Generative Models with the Method of Learned Moments.

Proceedings of the 35th International Conference on Machine Learning, 2018

2016

Unsupervised Learning of 3D Structure from Images.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

One-Shot Generalization in Deep Generative Models.

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Variational Inference with Normalizing Flows.

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Partial Membership and Factor Analysis.

Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

Semi-supervised Learning with Deep Generative Models.

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Stochastic Backpropagation and Approximate Inference in Deep Generative Models.

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Adaptive Hamiltonian and Riemann Manifold Monte Carlo.

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models.

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models.

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression.

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Expectation Propagation in Gaussian Process Dynamical Systems.

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning .

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Generalised Bayesian matrix factorisation models.

PhD thesis, 2011

2009

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process.

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Probabilistic non-negative tensor factorization using Markov chain Monte Carlo.

Proceedings of the 17th European Signal Processing Conference, 2009

2008

Bayesian Exponential Family PCA.

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Incremental Learning for Classification of Protein Sequences.

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Multi-class Protein Sequence Classification Using Fuzzy ARTMAP.

Proceedings of the IEEE International Conference on Systems, 2006

An Extension Neural Network and Genetic Algorithm for Bearing Fault Classification.

Proceedings of the International Joint Conference on Neural Networks, 2006