1 Outline • Motivation: characterise processes (quantum computation) Graphical reasoning

Source URL: dream.inf.ed.ac.uk

Graphical Model Approach to Pitch Tracking Xiao Li, Jonathan Malkin and Jeff Bilmes Department of Electrical Engineering University of Washington, Seattle {lixiao,jsm,bilmes}@ee.washington.edu

Source URL: melodi.ee.washington.edu

Monoidal Categories, Graphical Reasoning, and Quantum Computation Lucas Dixon and Aleks Kissinger CAM-CAD 2009 Abstract Graphs provide a natural mechanism for visualising many algebraic

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Mathematical Process—Representing The Ontario Curriculum, Mathematics, 2005 Students will create a variety of representations of mathematical ideas (e.g., numeric, geometric, algebraic, graphical, pictorial; on-screen

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Constrained Patterns, Part 3: Representing Constraint Sets Neighborhood constraint sets can be represented in several ways. For human understanding, graphical methods work best. For computer processing, textual represent

Source URL: www.cs.arizona.edu

Graphical reasoning in symmetric monoidal categories Lucas Dixon, University of Edinburgh Joint work with: Ross Duncan and Aleks Kissinger, University of Oxford 5 Nov 2009

Source URL: www.cs.le.ac.uk

Supplementary Information and Figures for “Consed: A Graphical Editor for Next-Generation Sequencing” by David Gordon and Phil Green S1 Input data requirements Consed requires reads and alignments either in BAM forma

Source URL: www.phrap.org

• Bioinformatics
• Molecular biology
• DNA sequencing
• Computational science
• Genomics
• Contig
• Consed
• Phrap
• Velvet assembler
• SAMtools
• ACE
• Expressed sequence tag

Object Categorization by Compositional Graphical Models Bj¨ orn Ommer and Joachim M. Buhmann ETH Zurich, Institute of Computational Science, CH-8092 Zurich, Switzerland

Source URL: hci.iwr.uni-heidelberg.de

Proof General meets IsaWin Combining Text-Based And Graphical User Interfaces David Aspinall 1 LFCS, School of Informatics, University of Edinburgh, U.K. Christoph L¨

Source URL: www.informatik.uni-bremen.de

Sequential Monte Carlo for graphical models: Graph decompositions and Divide-and-Conquer SMC Fredrik Lindsten Department of Engineering The University of Cambridge Cambridge, UK

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