“‘Data Visualization’ Tag”,2019-10-09 (typography, statistics, tech)⁠:

Bibliography for tag design/visualization, most recent first: 5 related tags, 112 annotations, & 82 links (parent).

• See Also
• Gwern
  • “Statistical Notes”, Gwern2014
• Links
  • “Diagramming Dante: Michelangelo Caetani’s Maps of the Divina Commedia (1855_169ya/1872_152ya)”, Dukes2024
  • “Hypercomputation without Bothering the Cactus People: Software Development for the DMT Headspace”, Flipper2024
  • “Song Pong: Synchronizing Pong to Music With Constrained Optimization”, Tao2024
  • “How Colorful Ribbon Diagrams Became the Face of Proteins”
  • “Rendering Protein Structures inside Cells at the Atomic Level With Unreal Engine”, Chen2023
  • “All Objects and Some Questions”, Lineweaver & Patel2023
  • “The Spinorial Ball: a Macroscopic Object of Spin-1/2”, Bernard-Bernardet et al 2023
  • “The Specious Art of Single-Cell Genomics”, Chari & Pachter2022
  • “Misleading Graphs in Context: Less Misleading Than Expected”, Driessen et al 2022
  • “Clock: 解説”
  • “Fooled by Beautiful Data: Visualization Esthetics Bias Trust in Science, News, and Social Media”, Lin & Thornton2022
  • “The Science of Visual Data Communication: What Works”, Franconeri et al 2021
  • “Can Humans Perform Mental Regression on a Graph? Accuracy and Bias in the Perception of Scatterplots”, Ciccione & Dehaene2021
  • “Truncating Bar Graphs Persistently Misleads Viewers”, Yang et al 2021d
  • “Multimodal Neurons in Artificial Neural Networks [CLIP]”, Goh et al 2021
  • “Visualizing MuZero Models”, Vries et al 2021
  • “Understanding RL Vision: With Diverse Environments, We Can Analyze, Diagnose and Edit Deep Reinforcement Learning Models Using Attribution”, Hilton et al 2020
  • “Questions About Trees”, Hayes2020
  • “When SimCity Got Serious: the Story of Maxis Business Simulations and SimRefinery”, Salvador2020
  • “Exploring Bayesian Optimization: Breaking Bayesian Optimization into Small, Sizeable Chunks”, Agnihotri & Batra2020
  • “Zoom In: An Introduction to Circuits—By Studying the Connections between Neurons, We Can Find Meaningful Algorithms in the Weights of Neural Networks”, Olah et al 2020
  • “Growing Neural Cellular Automata: Differentiable Model of Morphogenesis”, Mordvintsev et al 2020
  • “Visual Model Fit Estimation in Scatterplots and Distribution of Attention: Influence of Slope and Noise Level”, Reimann et al 2020
  • “Unraveling the JPEG: JPEG Images Are Everywhere in Our Digital Lives, but behind the Veil of Familiarity Lie Algorithms That Remove Details That Are Imperceptible to the Human Eye. This Produces the Highest Visual Quality With the Smallest File Size—But What Does That Look Like? Let’s See What Our Eyes Can’t See!”, Shehata2019
  • “How Low Can You Go? Detecting Style in Extremely Low Resolution Images”, Searston et al 2019
  • “On Binscatter”, Cattaneo et al 2019
  • “Multi-Stage Bean Machine Visualization: Advantages of Repeated Optimization”, Kennedy & Gwern2018
  • “GAN Dissection: Visualizing and Understanding Generative Adversarial Networks”, Bau et al 2018
  • “7 Weeks to Venice: History Through Isochronic Maps”
  • “Why Scatter Plots Suggest Causality, and What We Can Do about It”, Bergstrom & West2018
  • “Raincloud Plots: a Multi-Platform Tool for Robust Data Visualization”, Allen et al 2018
  • “The Simple but Ingenious System Taiwan Uses to Crowdsource Its Laws: VTaiwan Is a Promising Experiment in Participatory Governance. But Politics Is Blocking It from Getting Greater Traction”, Horton2018
  • “Good Sound, Good Research: How Audio Quality Influences Perceptions of the Research and Researcher”, Newman & Schwarz2018
  • “Sequence Modeling With CTC: A Visual Guide to Connectionist Temporal Classification, an Algorithm Used to Train Deep Neural Networks in Speech Recognition, Handwriting Recognition and Other Sequence Problems”, Hannun2017
  • “NIMA: Neural Image Assessment”, Talebi & Milanfar2017
  • “These Maps Reveal the Hidden Structures of Choose Your Own Adventure Books: If You Decide to See More, Click on This Story”, Laskow2017
  • “What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features”, Zhang et al 2017
  • Atlas of Oblique Maps, King2017
  • “The Esthetic-Usability Effect”, Moran2017
  • “A Neural Network Playground”, Smilkov & Carter2016
  • “LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks”, Strobelt et al 2016
  • “The Tail End”, waitbutwhy 2015
  • “Visualizing and Understanding Recurrent Networks”, Karpathy et al 2015
  • Elephas Anthropogenus, Westphal2015
  • “Reflections on How Designers Design With Data”, Bigelow et al 2014
  • “Your Life in Weeks”, Why 2014
  • “Neural Networks, Manifolds, and Topology”, Olah2014
  • “When Graphics Improve Liking but Not Learning from Online Lessons”, Sung & Mayer2012
  • “The Biological Basis of a Universal Constraint on Color Naming: Cone Contrasts and the Two-Way Categorization of Colors”, Xiao et al 2011
  • “Explorable Explanations”, Victor2011
  • “The Snowflake Man of Vermont”, Heidorn2011
  • “Tomas Lopez’s Geographic Atlas of Spain in the Peninsular War: A Methodology for Determining Errors”, San-Antonio-Gómez et al 2011
  • “Choose Your Own Adventure: One Book, Many Readings”, Swinehart2009
  • “Verbal Probability Expressions In National Intelligence Estimates: A Comprehensive Analysis Of Trends From The Fifties Through Post-9/11”, Kesselman2008
  • “The Architectural Relevance of Gordon Pask: Usman Haque Reviews the Contribution of Gordon Pask, the Resident Cybernetician on Cedric Price’s Fun Palace. He Describes Why in the 20 First Century the Work of This Early Proponent and Practitioner of Cybernetics Has Continued to Grow in Pertinence for Architects and Designers Interested in Interactivity”, Bettella2007
  • “A Systematic Review on Communicating With Patients about Evidence”, Trevena et al 2005
  • “Distinguishing Real Vs. Fake Tiger Penises [Identification Guides for Wildlife Law Enforcement No. 6]”, Yates2005
  • “Sparkline Theory and Practice”, Tufte2004
  • “The Efficacy of the ‘Mind Map’ Study Technique”, Farrand et al 2002
  • “Naked Objects: a Technique for Designing More Expressive Systems”, Pawson & Matthews2001
  • “What Do You Care What Other People Think § It’s As Simple As One, Two, Three”, Feynman2001
  • “SnowCrystals.com”, Libbrecht1999
  • “Feynman’s War: Modeling Weapons, Modeling Nature”, Galison1998
  • “Visual Explanations: Images and Quantities, Evidence and Narrative, Tufte1997”,
  • “Knowledge of the Territory”, Revel1991
  • “Role of Color in Perception of Attractiveness”, Radeloff1990
  • “Envisioning Information: Chapter 5, ‘Color and Information’, Pg83-86 [On Oliver Byrne’s Color Diagram Version of Euclid’s Elements]”, Tufte1990
  • Atlas Of Oblique Maps: A Collection Of Landform Portrayals Of Selected Areas Of The World, Alpha et al 1988
  • “Recent Works [Exploded-Diagram Sculptures]”, Peralta2024
  • “DLA—Diffusion Limited Aggregation”
  • “Sculptures”, Abel2024
  • “The World’s First Code-Free Sparkline Typeface: Displaying Charts in Text without Having to Use Code”
  • “GAN Dissection: Visualizing and Understanding Generative Adversarial Networks [Blog]”
  • “We Need Visual Programming. No, Not like That.”
  • “Visualizing Algorithms”
  • “Seeing Centuries”, Andrews2024
  • “Attention and Augmented Recurrent Neural Networks”
  • “Deconvolution and Checkerboard Artifacts”
  • “Using Artificial Intelligence to Augment Human Intelligence”
  • “Feature Visualization”
  • “Why Momentum Really Works”
  • “Research Debt”
  • “Differentiable Image Parameterizations”
  • “Activation Atlas”
  • “A Discussion of ‘Adversarial Examples Are Not Bugs, They Are Features’”
  • “A Discussion of ‘Adversarial Examples Are Not Bugs, They Are Features’: Learning from Incorrectly Labeled Data”
  • “Branch Specialization”
  • “Differentiable Self-Organizing Systems”
  • “Self-Classifying MNIST Digits”
  • “Adversarial Reprogramming of Neural Cellular Automata”
  • “Self-Organising Textures”
  • “Crystal Ball Trading Challenge”, Wealth2024
  • “Explorable Explanations”
  • “How to Visualize Data With Cartoonish Faces Ala Chernoff”
  • “Gaussian Belief Propagation”
  • “Create Elegant Data Visualizations Using the Grammar of Graphics”
  • “Beyond Weber’s Law: A Second Look at Ranking Visualizations of Correlation”
  • “Forebruary Perpetual Calendar”
  • “Hamiltonian Cycles on Ammann-Beenker Tilings”
  • “ORBIS: The Stanford Geospatial Network Model of the Roman World”
  • “Visualizing Bayes’ Theorem”
  • “Agnes Giberne’s The Story of the Sun, Moon, and Stars”
  • “Picturing a Voice: Margaret Watts Hughes and the Eidophone”
  • “From Fire Hazards to Family Trees: The Sanborn Fire Insurance Maps”
  • “StyleGAN for Evil: Trypophobia and Clockwork Oranging”
  • Envisioning Information
  • “New Look, Same Great Look”
  • “Towards Moore’s Law Software: Part 3 of 3”
  • “Visualization Series: Using Scatterplots and Models to Understand the Diamond Market (so You Don’t Get Ripped Off)”
  • “Inside the Secret World of Russia’s Cold War Mapmakers”
  • “The Soviet Military’s Eerily Detailed Guide to San Diego”
  • “Star Timelapse Revealing the Earth’s Rotation”, Rivest2024
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