NeuroScale: Novel Topographic Feature Extraction using RBF Networks. - David Lowe; Michael E. Tipping (NIPS, 1996)

Feed-Forward Neural Networks and Topographic Mappings for Exploratory Data Analysis. - David Lowe; Michael E. Tipping (Neural Comput. Appl., 1996)

Topographic mappings and feed-forward neural networks. - Michael E. Tipping (1996)

Probabilistic Visualisation of High-Dimensional Binary Data. - Michael E. Tipping (NIPS, 1998)

Shadow targets: A novel algorithm for topographic projections by radial basis functions. - Michael E. Tipping; David Lowe (Neurocomputing, 1998)

A Hierarchical Latent Variable Model for Data Visualization. - Christopher M. Bishop; Michael E. Tipping (IEEE Trans. Pattern Anal. Mach. Intell., 1998)

The Relevance Vector Machine. - Michael E. Tipping (NIPS, 1999)

Mixtures of Probabilistic Principal Component Analysers. - Michael E. Tipping; Christopher M. Bishop (Neural Comput., 1999)

Sparse Kernel Principal Component Analysis. - Michael E. Tipping (NIPS, 2000)

Variational Relevance Vector Machines. - Christopher M. Bishop; Michael E. Tipping (UAI, 2000)

A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds. - Michael E. Tipping; Bernhard Schölkopf (AISTATS, 2001)

A Variational Approach to Robust Regression. - Anita C. Faul; Michael E. Tipping (ICANN, 2001)

Analysis of Sparse Bayesian Learning. - Anita C. Faul; Michael E. Tipping (NIPS, 2001)

Sparse Bayesian Learning and the Relevance Vector Machine. - Michael E. Tipping (J. Mach. Learn. Res., 2001)

Bayesian Image Super-Resolution. - Michael E. Tipping; Christopher M. Bishop (NIPS, 2002)

Bayesian Inference: An Introduction to Principles and Practice in Machine Learning. - Michael E. Tipping (Advanced Lectures on Machine Learning, 2003)

Fast Marginal Likelihood Maximisation for Sparse Bayesian Models. - Michael E. Tipping; Anita C. Faul (AISTATS, 2003)

A variational approach to robust Bayesian interpolation. - Michael E. Tipping; Neil D. Lawrence (NNSP, 2003)

Bayesian extension to the language model for ad hoc information retrieval. - Hugo Zaragoza; Djoerd Hiemstra; Michael E. Tipping (SIGIR, 2003)

Use of the Zero-Norm with Linear Models and Kernel Methods. - Jason Weston; André Elisseeff; Bernhard Schölkopf; Michael E. Tipping (J. Mach. Learn. Res., 2003)

Variational inference for Student-t models: Robust Bayesian interpolation and generalised component analysis. - Michael E. Tipping; Neil D. Lawrence (Neurocomputing, 2005)

Understanding forecast reconciliation. - Ross Hollyman; Fotios Petropoulos; Michael E. Tipping (Eur. J. Oper. Res., 2021)