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</a> </div> <h2 class="home-page-title"> Trending Research </h2> </div> <div class="col-lg-6 index-group"> <div style="float: right;" class="btn-group btn-group-sm pull-right home-page-navigation" role="group"> </div> </div> </div> </div> <div class="infinite-container text-center home-page"> <div class="row infinite-item item paper-card"> <!-- 2242654 --> <div class="col-lg-3 item-image-col"> <a href="/paper/a-user-focused-approach-to-evaluating"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/2311.18258.jpg');"> </div> </a> </div> <div class="col-lg-9 item-col"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/a-user-focused-approach-to-evaluating">A User-Focused Approach to Evaluating Probabilistic and Categorical Forecasts</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg 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onclick="captureOutboundLink('https://github.com/nci/scores'); return true;" style="font-size:13px"> nci/scores </a> </span> • <span class="author-name-text item-date-pub">30 Nov 2023</span> </p> <p class="item-strip-abstract">A user-focused verification approach for evaluating probability forecasts of binary outcomes (also known as probabilistic classifiers) is demonstrated that is (i) based on proper scoring rules, (ii) focuses on user decision thresholds, and (iii) provides actionable insights.</p> <div class="sota"> </div> <p> <span class="badge badge-primary badge-primary-nohover">Applications</span> </p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 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item-image-col"> <a href="/paper/ruptures-change-point-detection-in-python"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/papergithubrepo/pgr-0000029269-07227649.jpg');"> </div> </a> </div> <div class="col-lg-9 item-col"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/ruptures-change-point-detection-in-python">ruptures: change point detection in Python</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/deepcharles/ruptures" onclick="captureOutboundLink('https://github.com/deepcharles/ruptures'); return true;" style="font-size:13px"> deepcharles/ruptures </a> </span> • <span class="author-name-text item-date-pub">2 Jan 2018</span> </p> <p class="item-strip-abstract">ruptures is a Python library for offline change point detection.</p> <div class="sota"> </div> <p> <span class="badge badge-primary badge-primary-nohover">Computation</span> <span class="badge 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208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> <div class="row infinite-item item paper-card"> <!-- 240605 --> <div class="col-lg-3 item-image-col"> <a href="/paper/a-large-scale-analysis-of-racial-disparities"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/papergithubrepo/pgr-0000240605-ce121fc3.jpg');"> </div> </a> </div> <div class="col-lg-9 item-col"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/a-large-scale-analysis-of-racial-disparities">A large-scale analysis of racial disparities in police stops across the United States</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/rfordatascience/tidytuesday" onclick="captureOutboundLink('https://github.com/rfordatascience/tidytuesday'); return true;" style="font-size:13px"> rfordatascience/tidytuesday </a> </span> • <span class="author-name-text item-date-pub">18 Jun 2017</span> </p> <p class="item-strip-abstract">We find that black drivers are stopped more often than white drivers relative to their share of the driving-age population, but that Hispanic drivers are stopped less often than whites.</p> <div class="sota"> </div> <p> <span class="badge badge-primary badge-primary-nohover">Applications</span> </p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 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<!-- 666839 --> <div class="col-lg-3 item-image-col"> <a href="/paper/nilmtk-an-open-source-toolkit-for-non"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/1404.3878.jpg');"> </div> </a> </div> <div class="col-lg-9 item-col"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/nilmtk-an-open-source-toolkit-for-non">NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/nilmtk/nilmtk" onclick="captureOutboundLink('https://github.com/nilmtk/nilmtk'); return true;" style="font-size:13px"> nilmtk/nilmtk </a> </span> • <span class="author-name-text item-date-pub">15 Apr 2014</span> </p> <p class="item-strip-abstract">We demonstrate the range of reproducible analyses which are made possible by our toolkit, including the analysis of six publicly available data sets and the evaluation of both benchmark disaggregation algorithms across such data sets.</p> <div class="sota"> </div> <p> <span class="badge badge-primary badge-primary-nohover">Applications</span> </p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M394 480a16 16 0 0 1-9.39-3L256 383.76 127.39 477a16 16 0 0 1-24.55-18.08L153 310.35 23 221.2a16 16 0 0 1 9-29.2h160.38l48.4-148.95a16 16 0 0 1 30.44 0l48.4 149H480a16 16 0 0 1 9.05 29.2L359 310.35l50.13 148.53A16 16 0 0 1 394 480z"/></svg></span> 854</span> </div> <div class="stars-accumulated text-center"> 0.01 stars / hour </div> <div class="entity" style="margin-bottom: 20px;"> <a href="/paper/nilmtk-an-open-source-toolkit-for-non" class="badge badge-light badge-stat"> <span class=" icon-wrapper icon-ion" data-name="document"><svg 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14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> <div class="row infinite-item item paper-card"> <!-- 2282787 --> <div class="col-lg-3 item-image-col"> <a href="/paper/pydmd-a-python-package-for-robust-dynamic"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/2402.07463.jpg');"> </div> </a> </div> <div class="col-lg-9 item-col"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/pydmd-a-python-package-for-robust-dynamic">PyDMD: A Python package for robust dynamic mode decomposition</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/pydmd/pydmd" onclick="captureOutboundLink('https://github.com/pydmd/pydmd'); return true;" style="font-size:13px"> pydmd/pydmd </a> </span> • <span class="author-name-text item-date-pub">12 Feb 2024</span> </p> <p class="item-strip-abstract">The method's linear algebra-based formulation additionally allows for a variety of optimizations and extensions that make the algorithm practical and viable for real-world data analysis.</p> <div class="sota"> </div> <p> <span class="badge badge-primary badge-primary-nohover">Computation</span> <span class="badge badge-primary badge-primary-nohover">Systems and Control</span> <span class="badge badge-primary badge-primary-nohover">Systems and Control</span> <span class="badge badge-primary badge-primary-nohover">Dynamical Systems</span> <span class="badge badge-primary badge-primary-nohover">Computational 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56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> Code </a> <br/> </div> </div> </div> </div> </div> <div class="row infinite-item item paper-card"> <!-- 1729668 --> <div class="col-lg-3 item-image-col"> <a href="/paper/statistical-consequences-of-fat-tails-real"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/2001.10488.jpg');"> </div> </a> </div> <div class="col-lg-9 item-col"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/statistical-consequences-of-fat-tails-real">Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 0-52.9-33.5-52.9-33.5-10.2-26.5-24.9-33.6-24.9-33.6-19.5-13.7-.1-14.1 1.4-14.1h.1c22.5 2 34.3 23.8 34.3 23.8 11.2 19.6 26.2 25.1 39.6 25.1a63 63 0 0 0 25.6-6c2-14.8 7.8-24.9 14.2-30.7-49.7-5.8-102-25.5-102-113.5 0-25.1 8.7-45.6 23-61.6-2.3-5.8-10-29.2 2.2-60.8a18.64 18.64 0 0 1 5-.5c8.1 0 26.4 3.1 56.6 24.1a208.21 208.21 0 0 1 112.2 0c30.2-21 48.5-24.1 56.6-24.1a18.64 18.64 0 0 1 5 .5c12.2 31.6 4.5 55 2.2 60.8 14.3 16.1 23 36.6 23 61.6 0 88.2-52.4 107.6-102.3 113.3 8 7.1 15.2 21.1 15.2 42.5 0 30.7-.3 55.5-.3 63 0 5.4 3.1 11.5 11.4 11.5a19.35 19.35 0 0 0 4-.4C415.9 449.2 480 363.1 480 261.7 480 134.9 379.7 32 256 32z"/></svg></span> <a href="https://github.com/FergM/fattails" onclick="captureOutboundLink('https://github.com/FergM/fattails'); return true;" style="font-size:13px"> FergM/fattails </a> </span> • <span class="author-name-text item-date-pub">24 Jan 2020</span> </p> <p class="item-strip-abstract">The monograph investigates the misapplication of conventional statistical techniques to fat tailed distributions and looks for remedies, when possible.</p> <div class="sota"> </div> <p> <span class="badge badge-primary badge-primary-nohover">Other Statistics</span> <span class="badge badge-primary badge-primary-nohover">Risk Management</span> <span class="badge badge-primary badge-primary-nohover">Applications</span> <span class="badge badge-primary badge-primary-nohover">Methodology</span> </p> </div> <div class="col-lg-3 item-interact text-center"> <div class="entity-stars"> <span class="badge badge-secondary"><span class=" icon-wrapper icon-ion" data-name="star"><svg xmlns="http://www.w3.org/2000/svg" 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</div> </div> </div> </div> </div> <div class="row infinite-item item paper-card"> <!-- 1792142 --> <div class="col-lg-3 item-image-col"> <a href="/paper/maars-tidy-inference-under-the-models-as"> <div class="item-image" style="background-image: url('https://production-media.paperswithcode.com/thumbnails/paper/2106.11188.jpg');"> </div> </a> </div> <div class="col-lg-9 item-col"> <div class="row"> <div class="col-lg-9 item-content"> <h1><a href="/paper/maars-tidy-inference-under-the-models-as">maars: Tidy Inference under the 'Models as Approximations' Framework in R</a></h1> <p class="author-section" style="padding-top:2px"> <span class="item-github-link"> <span class=" icon-wrapper icon-ion" data-name="logo-github"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M256 32C132.3 32 32 134.9 32 261.7c0 101.5 64.2 187.5 153.2 217.9a17.56 17.56 0 0 0 3.8.4c8.3 0 11.5-6.1 11.5-11.4 0-5.5-.2-19.9-.3-39.1a102.4 102.4 0 0 1-22.6 2.7c-43.1 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