{"id":963642,"date":"2023-08-30T09:00:00","date_gmt":"2023-08-30T16:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?p=963642"},"modified":"2023-08-23T13:56:08","modified_gmt":"2023-08-23T20:56:08","slug":"research-focus-week-of-august-28-2023","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/research\/blog\/research-focus-week-of-august-28-2023\/","title":{"rendered":"Research Focus: Week of August 28, 2023"},"content":{"rendered":"\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1400\" height=\"264\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-banner-1400x264-1.png\" alt=\"Microsoft Research Focus 23 | Week of August 28, 2023\" class=\"wp-image-963663\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-banner-1400x264-1.png 1400w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-banner-1400x264-1-300x57.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-banner-1400x264-1-1024x193.png 1024w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-banner-1400x264-1-768x145.png 768w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-banner-1400x264-1-240x45.png 240w\" sizes=\"(max-width: 1400px) 100vw, 1400px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-pullquote\"><blockquote><p><em class=\"\">Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code\/datasets, new hires and other milestones from across the research community at Microsoft.<\/em><\/p><\/blockquote><\/figure>\n\n\n<aside id=accordion-a042bbc7-357c-4147-8506-94e47ebccc24 class=\"msr-table-of-contents-block accordion mb-5 pb-0\" data-bi-aN=\"table-of-contents\">\n\t<button class=\"btn btn-collapse bg-gray-100 mb-0 display-flex justify-content-between\" type=\"button\" data-mount=\"collapse\" data-target=\"#accordion-collapse-a042bbc7-357c-4147-8506-94e47ebccc24\" aria-expanded=\"true\" aria-controls=\"accordion-collapse-a042bbc7-357c-4147-8506-94e47ebccc24\">\n\t\t<span class=\"msr-table-of-contents-block__label subtitle\">In this article<\/span>\n\t\t<span class=\"msr-table-of-contents-block__current mr-4 text-gray-600 font-weight-normal\" aria-hidden=\"true\"><\/span>\n\t<\/button>\n\t<div id=\"accordion-collapse-a042bbc7-357c-4147-8506-94e47ebccc24\" class=\"msr-table-of-contents-block__collapse-wrapper collapse show\" data-parent=\"#accordion-a042bbc7-357c-4147-8506-94e47ebccc24\">\n\t\t<div class=\"accordion-body bg-gray-100 border-top pt-4\">\n\t\t\t<ol class=\"msr-table-of-contents-block__list\">\n\t\t\t\t\t\t\t\t\t<li class=\"msr-table-of-contents-block__list-item\">\n\t\t\t\t\t\t<a href=\"#an-illusion-of-predictability-in-scientific-results-even-experts-confuse-inferential-uncertainty-and-outcome-variability\" class=\"msr-table-of-contents-block__list-item-link\">An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability<\/a>\n\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<li class=\"msr-table-of-contents-block__list-item\">\n\t\t\t\t\t\t<a href=\"#figure-simple-and-efficient-unsupervised-node-representations-with-filter-augmentations\" class=\"msr-table-of-contents-block__list-item-link\">FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations<\/a>\n\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<li class=\"msr-table-of-contents-block__list-item\">\n\t\t\t\t\t\t<a href=\"#kathleen-sullivan-named-to-insider-s-30-under-40-in-healthcare-list\" class=\"msr-table-of-contents-block__list-item-link\">Kathleen Sullivan named to Insider\u2019s 30 under 40 in healthcare list<\/a>\n\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t<\/ul>\n\t\t<\/div>\n\t<\/div>\n\t<span class=\"msr-table-of-contents-block__progress-bar\"><\/span>\n<\/aside>\n\n\n\n<h3 class=\"wp-block-heading h6 has-blue-color has-text-color\" id=\"new-research\">NEW RESEARCH<\/h3>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"an-illusion-of-predictability-in-scientific-results-even-experts-confuse-inferential-uncertainty-and-outcome-variability\">An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability<\/h2>\n\n\n\n<p>In many fields, practitioners focus on inference (precisely estimating an unknown quantity, such as a population average) instead of prediction (forecasting individual outcomes). In a <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/an-illusion-of-predictability-in-scientific-results-even-experts-confuse-inferential-uncertainty-and-outcome-variability\/\">newly published article<\/a>, researchers from Microsoft demonstrate that this focus on inference over prediction can mislead readers into thinking that the results of scientific studies are more definitive than they actually are.<\/p>\n\n\n\n<p>Through a series of randomized experiments, the researchers demonstrate that this confusion arises for one of the most basic ways of presenting statistical findings and affects even experts whose jobs involve producing and interpreting such results, including medical professionals, data scientists, and tenure-track faculty.&nbsp; In contrast, the paper shows that communicating both inferential and predictive information side by side provides a simple and effective alternative, leading to calibrated interpretations of scientific results.<\/p>\n\n\n\n<p>This article was published in the Proceedings of the National Academy of Sciences (PNAS).<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-1 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-outline is-style-outline--972dfbf116bb195194d31cb68959ef02\"><a data-bi-type=\"button\" class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/an-illusion-of-predictability-in-scientific-results-even-experts-confuse-inferential-uncertainty-and-outcome-variability\/\" target=\"_blank\" rel=\"noreferrer noopener\">Read the article<\/a><\/div>\n\n\n\n<div class=\"wp-block-button is-style-fill-github\"><a data-bi-type=\"button\" class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/github.com\/jhofman\/illusion-of-predictability\" target=\"_blank\" rel=\"noreferrer noopener\">Data and code<\/a><\/div>\n<\/div>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n\t<div class=\"border-bottom border-top border-gray-300 mt-5 mb-5 msr-promo text-center text-md-left alignwide\" data-bi-aN=\"promo\" data-bi-id=\"1085502\">\n\t\t\n\n\t\t<p class=\"msr-promo__label text-gray-800 text-center text-uppercase\">\n\t\t<span class=\"px-4 bg-white display-inline-block font-weight-semibold small\">Spotlight: Blog post<\/span>\n\t<\/p>\n\t\n\t<div class=\"row pt-3 pb-4 align-items-center\">\n\t\t\t\t\t\t<div class=\"msr-promo__media col-12 col-md-5\">\n\t\t\t\t<a class=\"bg-gray-300\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/blog\/research-focus-week-of-september-9-2024\/\" aria-label=\"Research Focus: Week of September 9, 2024\" data-bi-cN=\"Research Focus: Week of September 9, 2024\" target=\"_blank\">\n\t\t\t\t\t<img decoding=\"async\" class=\"w-100 display-block\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/09\/RF49-BlogHeroFeature-1400x788-1.jpg\" alt=\"Research Focus | September 9, 2024\" \/>\n\t\t\t\t<\/a>\n\t\t\t<\/div>\n\t\t\t\n\t\t\t<div class=\"msr-promo__content p-3 px-5 col-12 col-md\">\n\n\t\t\t\t\t\t\t\t\t<h2 class=\"h4\">Research Focus: Week of September 9, 2024<\/h2>\n\t\t\t\t\n\t\t\t\t\t\t\t\t<p class=\"large\">Investigating vulnerabilities in LLMs; A novel total-duration-aware (TDA) duration model for text-to-speech (TTS); Generative expert metric system through iterative prompt priming; Integrity protection in 5G fronthaul networks.<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t<div class=\"wp-block-buttons justify-content-center justify-content-md-start\">\n\t\t\t\t\t<div class=\"wp-block-button\">\n\t\t\t\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/blog\/research-focus-week-of-september-9-2024\/\" class=\"btn btn-brand glyph-append glyph-append-chevron-right\" aria-label=\"Read more\" data-bi-cN=\"Research Focus: Week of September 9, 2024\" target=\"_blank\">\n\t\t\t\t\t\t\tRead more\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div><!--\/.msr-promo__content-->\n\t<\/div><!--\/.msr-promo__inner-wrap-->\n\t<\/div><!--\/.msr-promo-->\n\t\n\n\n<h3 class=\"wp-block-heading h6 has-blue-color has-text-color\" id=\"new-research-1\">NEW RESEARCH<\/h3>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"figure-simple-and-efficient-unsupervised-node-representations-with-filter-augmentations\">FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations<\/h2>\n\n\n\n<p>Contrastive learning is a powerful method for unsupervised graph representation learning. It is typically deployed on <em>homophilic<\/em> tasks, where task labels strongly correlate with the graph\u2019s structure. However, these representations struggle when dealing with <em>heterophilic<\/em> tasks, where edges tend to connect nodes with different labels.<\/p>\n\n\n\n<p>Several papers have tackled the problem of heterophily by leveraging information from both low and high frequency components. Yet these methods operate in semi-supervised settings, and the extension of these ideas in unsupervised learning still needs to be explored.<\/p>\n\n\n\n<p>In a new paper: <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/figure-simple-and-efficient-unsupervised-node-representations-with-filter-augmentations\/\">FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations<\/a>, researchers from Microsoft propose using filter banks for learning representations that can cater to both heterophilic and homophilic tasks. They address the related computational and storage burdens by sharing the encoder across these various filter views, and by learning a low-dimensional representation which is projected to high dimensions using Random Fourier Features. FiGURe achieves a gain of up to 4.4%, compared to the state-of-the-art unsupervised models, across all datasets in consideration, both homophilic and heterophilic.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-2 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-outline is-style-outline--03d967ace37f346e5423737856b4b6dd\"><a data-bi-type=\"button\" class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/figure-simple-and-efficient-unsupervised-node-representations-with-filter-augmentations\/\">Read the paper<\/a><\/div>\n\n\n\n<div class=\"wp-block-button is-style-fill-github\"><a data-bi-type=\"button\" class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/github.com\/microsoft\/figure\" target=\"_blank\" rel=\"noreferrer noopener\">View the code<\/a><\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-dots\"\/>\n\n\n\n<h3 class=\"wp-block-heading h6 has-blue-color has-text-color\" id=\"award\">AWARD<\/h3>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"kathleen-sullivan-named-to-insider-s-30-under-40-in-healthcare-list\">Kathleen Sullivan named to Insider\u2019s 30 under 40 in healthcare list<\/h2>\n\n\n\n<p>Microsoft Research congratulates&nbsp;<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/kasull\/\">Kathleen Sullivan<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>&nbsp;for being named to&nbsp;Insider&#8217;s list of <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.businessinsider.com\/30-leaders-under-40-changing-healthcare-2023\" target=\"_blank\" rel=\"noreferrer noopener\">30 under 40 forging a new future in healthcare<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>. After a competitive nomination and interview, Kathleen was selected for this inspiring list of \u201centrepreneurs, scientists, doctors, and business leaders who are transforming the healthcare industry.\u201d<\/p>\n\n\n\n<p>As senior director of strategy and operations within the health and life sciences division of Microsoft Research, Sullivan helps steer the company\u2019s investments in AI. She helped engineer a Microsoft collaboration with Nuance Technologies&#8211;a precursor to Microsoft&#8217;s acquisition of Nuance in 2021. In 2018, Sullivan helped secure Microsoft&#8217;s partnership with Adaptive Biotechnologies to <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.businesswire.com\/news\/home\/20180104005464\/en\/Adaptive-Biotechnologies-Announces-Partnership-with-Microsoft-to-Decode-the-Human-Immune-System-to-Improve-the-Diagnosis-of-Disease\" target=\"_blank\" rel=\"noreferrer noopener\">map the human immune system<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>.&nbsp;<\/p>\n\n\n\n<p class=\"has-text-align-center\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.businessinsider.com\/30-leaders-under-40-changing-healthcare-2023\" target=\"_blank\" rel=\"noreferrer noopener\">Read the Insider article<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><br>(subscription required)<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this issue: An illusion of predictability in scientific results; Kathleen Sullivan named to Insider\u2019s 30 under 40 in healthcare list; FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations.<\/p>\n","protected":false},"author":42183,"featured_media":963669,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"categories":[1],"tags":[],"research-area":[13556,13559],"msr-region":[],"msr-event-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-impact-theme":[],"msr-promo-type":[],"msr-podcast-series":[],"class_list":["post-963642","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-blog","msr-research-area-artificial-intelligence","msr-research-area-social-sciences","msr-locale-en_us"],"msr_event_details":{"start":"","end":"","location":""},"podcast_url":"","podcast_episode":"","msr_research_lab":[199571],"msr_impact_theme":[],"related-publications":[],"related-downloads":[],"related-videos":[],"related-academic-programs":[],"related-groups":[144903],"related-projects":[],"related-events":[],"related-researchers":[],"msr_type":"Post","featured_image_thumbnail":"<img width=\"960\" height=\"540\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-960x540.png\" class=\"img-object-cover\" alt=\"Microsoft Research Focus 23 | Week of August 14, 2023\" decoding=\"async\" loading=\"lazy\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-960x540.png 960w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-300x169.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-1024x576.png 1024w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-768x432.png 768w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-1066x600.png 1066w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-655x368.png 655w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-343x193.png 343w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-240x135.png 240w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-640x360.png 640w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1-1280x720.png 1280w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/08\/RF23-blog-hero-1400x788-1.png 1400w\" sizes=\"(max-width: 960px) 100vw, 960px\" \/>","byline":"","formattedDate":"August 30, 2023","formattedExcerpt":"In this issue: An illusion of predictability in scientific results; Kathleen Sullivan named to Insider\u2019s 30 under 40 in healthcare list; FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations.","locale":{"slug":"en_us","name":"English","native":"","english":"English"},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/963642"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/users\/42183"}],"replies":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/comments?post=963642"}],"version-history":[{"count":11,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/963642\/revisions"}],"predecessor-version":[{"id":966798,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/963642\/revisions\/966798"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/963669"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=963642"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/categories?post=963642"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/tags?post=963642"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=963642"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=963642"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=963642"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=963642"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=963642"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=963642"},{"taxonomy":"msr-promo-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-promo-type?post=963642"},{"taxonomy":"msr-podcast-series","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-podcast-series?post=963642"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}