Dominik Endres' Home PageUniversity of St Andrews
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Concept lattice of my work |
| Legend: the graph below shows a concept lattice of my work. Each node represents a formal concept, the concept whose extent and intent are displayed on this page is highlighted in green. The graph is interactive, you can jump to a concept by clicking on it. The top concept links to my homepage. Think of the intent as the set of tags shared by the set of papers or presentations which form the extent of a concept (below the graph). Concepts are partially ordered: concept A > concept B if extent of A is a superset of B's extent (or conversely, if the intent of A is a subset of B's intent). An arrow from A to B means that A > B. I used reduced labelling, i.e. a tag is only shown in the largest concept which contains it. If you'd like to know more about Formal Concept Analysis, here is a good place to start! |
Intent: publication, Bayesian methods, Spiketrain analysis |
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Extent: |
 D. Endres, M. Oram, J. Schindelin and P. Földiák, Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms,pp. 393-400, Advances in Neural Information Processing Systems 20, MIT Press, Cambridge, MA, 2008 |
| D. Endres and P. Földiák, Exact Bayesian Bin Classification: a fast alternative to Bayesian Classification and its application to neural response analysis, Journal of Computational Neuroscience, 24(1): 24-35, 2008. DOI: 10.1007/s10827-007-0039-5. The original publication is available at www.springerlink.com |
| D. Endres and P. Földiák, Bayesian bin distribution inference and mutual information, IEEE Transactions on Information Theory, vol. 51, no. 11, pp. 3766-3779, November 2005 |