The Visual Computing Group, led by Hanspeter Pfister, explores and provides visual analysis tools and methods to help scientists and researchers better process and understand large, multi-dimensional data sets in various domains such as neuroscience, genomics, systems biology, astronomy, and medicine.
Projects
Latest Publications
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Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data
— To appear in IEEE Transactions on Visualization and Computer Graphics.
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FDive: Learning Relevance Models using Pattern-based Similarity Measures
— To appear in IEEE Transactions on Visualization and Computer Graphics.
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Guiro: User-Guided Matrix Reordering
— To appear in IEEE Transactions on Visualization and Computer Graphics.
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Pattern-Driven Navigation in 2D Multiscale Visualizations with Scalable Insets
— To appear in IEEE Transactions on Visualization and Computer Graphics.
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Visual Interaction with Deep Learning Models through Collaborative Semantic Inference
— To appear in IEEE Transactions on Visualization and Computer Graphics.
News
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Harvard VCG
@HarvardVCGFinally, Frederik Dennig, Thomas Polk, Zudy Lin, Tobias Schreck @hpfister & @michaelbehrisch developed FDive (… -
Harvard VCG
@HarvardVCGIn Collaborative Semantic Inference (https://t.co/25IKlmwMQI), @sebgehr @hen_str @robertK65542738 @hpfister @snpvp… -
Harvard VCG
@HarvardVCGOur second VAST paper (https://t.co/igbyhZXp9J) by @michaelbehrisch @hpfister & Tobias Schreck is about User-Guided… -
Harvard VCG
@HarvardVCGAt InfoVis, @flekschas @michaelbehrisch @benjbach @pkerpedjiev @ngehlenborg @hpfister will present Pattern-Driven N… -
Harvard VCG
@HarvardVCGOur first VAST paper (https://t.co/h76YxKwbZ0) is about Combining Unsupervised and Supervised Learning for Hierarch…