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HTTP/1.1 200 OKDate: Fri, 13 Sep 2024 11:20:54 GMTServer: ApacheCache-Control: max-age600Expires: Fri, 13 Sep 2024 11:30:54 GMTVary: Accept-Encoding,User-AgentContent-Length: 21317Content-Type: text/html; charsetUTF-8 html>head>meta propertyog:image contenthttp://www.yisongyue.com/images/Caltech_LOGO-BLACK-RGB.jpg>title>Yisong Yue | Machine Learning Professor @ Caltech/title>link relshortcut icon typeimage/x-icon href/navicon2.png /> META nameDescription contentYisong Yue is a professor in the Computing and Mathematical Sciences Department at the California Institute of Technology. His research interests lie primarily in the theory and application of statistical machine learning./>script languagejavascript src/jquery.min.js>/script>script languagejavascript src/jquery-ui.min.js>/script>script languagejavascript src/yyue.js>/script>script>var main_height455;$( document ).ready(function() { if($(#main).height() main_height) { $(#main).height(main_height); } setTimeout(function(){ if($(#main).height() main_height) { $(#main).height(main_height); } },200); if(window.location.hash ! ) { jump_to(window.location.hash); }});/script>link relstylesheet typetext/css href/yue2.css>/head>body>div idheader> div classleft_header> font classname>Yisong Yue |/font> Machine Learning Professor @ a hrefhttp://www.caltech.edu>img classlogo src/images/caltech_logo.png >/a> /div> div classright_header> a classnavbar href/index.php>Home/a> | a classnavbar href/news.php>News/a> | a classnavbar href/about.php>About/a> | a classnavbar href/group.php>Group/a> | a classnavbar href/research.php>Research/a> | a classnavbar href/teaching.php>Teaching/a> | a classnavbar href/etc.php>Etc./a> /div>/div>div idmain>div idleft_main>div classitem2>div classcentered>a href/images/yue_headshot.jpg>img idheadshot src/images/yue_headshot.jpg>/a>/div>/div>div classitem>b>Yisong Yue/b> (he/him) br>California Institute of Technologybr>1200 E. California Blvd. br>CMS, 305-16br>Pasadena, CA 91125 br>br>b>Office:/b> 303 Annenbergbr>br>b>a classnavbar hrefcontact.php>Contact Information >/a>/b>br>br>a hrefhttps://www.quora.com/Yisong-Yue/answers>img src/images/icon_quora_small.png height20 width20 />/a>a hrefhttps://twitter.com/yisongyue>img src/images/icon_twitter_small.jpg height20 width20 />/a>a hrefhttps://www.linkedin.com/in/yisongyue/>img src/images/linkedin-icon-small.png height20 width20 />/a>a hrefhttps://scholar.google.com/citations?hlen&usertEk4qo8AAAAJ&sortbypubdate>img src/images/gscholar.png height20 width20 />/a>a hrefhttps://www.semanticscholar.org/author/Yisong-Yue/1740159>img src/images/icon-semantic-scholar.png height20 width20 />/a>a hrefhttps://dblp.uni-trier.de/pers/hd/y/Yue:Yisong>img src/images/dblp.jpg height20 width20 />/a>a hrefhttp://www.flickr.com/photos/yisongyue/>img src/images/flickr_icon_small.jpg height20 width20 />/a>/div>/div>div idright_main>div classitem>div classtitle>About/div>I am a professor of a hrefhttp://www.cms.caltech.edu>Computing and Mathematical Sciences/a> at the a hrefhttp://www.caltech.edu>California Institute of Technology/a>. My research interests lie primarily in a hrefhttp://en.wikipedia.org/wiki/Machine_learning>machine learning/a>, and span the entire theory-to-application spectrum from foundational advances all the way to deployment in real systems. I work closely with domain experts to understand the frontier challenges in applied machine learning, distill those challenges into mathematically precise formulations, and develop novel methods to tackle them. br>br>b>Asari AI/b>: I am a founding advisor for a hrefhttps://asari.ai/>Asari AI/a>, where I help design AI co-inventors (AI agents that can plan, abstract, and verify complex design tasks).br>br> b>Latitude AI/b>: I am currently a (part-time) Principal Scientist at a hrefhttps://lat.ai/>Latitude AI/a>, where I work on machine learning approaches to behavior modeling and motion planning for autonomous driving. br>br> b>ICLR 2025/b>: I am serving as the General Chair at a hrefhttps://iclr.cc/>ICLR 2025/a>. The Program Chairs are a hrefhttps://www.cs.columbia.edu/~vondrick/>Carl Vondrick/a> (SPC), a hrefhttps://roseyu.com/>Rose Yu/a>, a hrefhttps://vnpeng.net/>Violet Peng/a>, a hrefhttps://www.feisha.org/>Fei Sha/a>, a hrefhttps://animesh.garg.tech/>Animesh Garg/a>.div classreadmore> a classnavbar hrefabout.php>about me >/a> br>a classnavbar hrefresearch.php>research >/a>/div>/div>div classitem>div classtitle>Diversity, Equity & Inclusion/div>I am committed to promoting diversity, equity, and inclusion in my research group, in my courses, within the CMS department, at Caltech more broadly, and within my research communities.ul>li>b>Diversity/b> -- I recognize that diversity, in all its shapes and forms, strengthens us both culturally and intellectually. li>b>Equity/b> -- I will fight for equal treatment of all people, regardless of race, gender, sexual orientation, or any other attributes that do not define a persons academic and research potential.li>b>Inclusion/b> -- I will work to create an inclusive working environment, so that everyone feels their voices are heard and their contributions are recognized./ul>Read more about diversity, equity, and inclusion at the a hrefhttps://cms.caltech.edu/about/diversity>CMS Department/a>and a hrefhttps://eas.caltech.edu/dei>EAS Division/a> at Caltech./div>div classitem>div classtitle>Current Research/div>My current research interests can be broadly organized into three overlapping groups:br>br>b>AI for Autonomy/b>: study how AI methods can enable novel capabilities in autonomous systems; characterize and address key technical bottlenecks (e.g., data-driven safety guarantees); deploy in real systems.details>summary>i>b>Selected Publications/b>/i>/summary>ul>li classwide>b>Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies/b>br>Ivan Dario Jimenez Rodriguez*, Noel Csomay-Shanklin*, Yisong Yue, Aaron D. Amesbr>i>Conference on Learning for Dynamics and Control (L4DC)/i>, June 2022.br>a hrefhttps://arxiv.org/abs/2204.08120>arxiv/a>a hrefhttps://www.youtube.com/watch?v8TeXd0AYtpA>video/a>/li> li classwide>b>Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds/b>br>Michael O’Connell*, Guanya Shi*, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chungbr>i>Science Robotics/i>, May 2022.br>a hrefhttps://arxiv.org/abs/2205.06908>arxiv/a>a hrefhttps://www.science.org/doi/10.1126/scirobotics.abm6597>online/a>a hrefhttps://github.com/aerorobotics/neural-fly>code/a>a hrefhttps://youtu.be/TuF9teCZX0U>video/a>a hrefhttps://www.caltech.edu/about/news/rapid-adaptation-of-deep-learning-teaches-drones-to-survive-any-weather>press release/a>/li>li classwide>b>MLNav: Learning to Safely Navigate on Martian Terrains/b>br>Shreyansh Daftry, Neil Abcouwer, Tyler Del Sesto, Siddarth Venkatraman, Jialin Song, Lucas Igel, Amos Byon, Ugo Rosolia, Yisong Yue, Masahiro Onobr>i>IEEE Robotics and Automation Letters (RA-L)/i>, May 2022br>a hrefhttps://arxiv.org/abs/2203.04563>conference/a>a hrefhttps://ieeexplore.ieee.org/document/9729506>journal/a>a hrefhttps://www.youtube.com/watch?v5LhAry9zIB4>video/a>/li>li classwide>b>GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End Learning/b>br>Benjamin Rivière, Wolfgang Hoenig, Yisong Yue, Soon-Jo Chungbr>i>IEEE Robotics and Automation Letters (RA-L)/i>, June 2020.br>font classaward>(Best Paper Nomination)/font>br>a hrefhttps://ieeexplore.ieee.org/document/9091314>pdf/a>a hrefhttps://arxiv.org/abs/2002.11807>arxiv/a>a hrefhttps://www.youtube.com/watch?vz9LjSfLfG6c>demo video/a>/li>li classwide>b>Preference-Based Learning for Exoskeleton Gait Optimization/b>br>Maegan Tucker*, Ellen Novoseller*, Claudia Kann, Yanan Sui, Yisong Yue, Joel Burdick, Aaron D. Amesbr>i>International Conference on Robotics and Automation (ICRA)/i>, May 2020.br>font classaward>(Best Paper Award)/font>br>a hrefpublications/icra2020_cospar.pdf>pdf/a>a hrefhttps://arxiv.org/abs/1909.12316>arxiv/a>a hrefhttps://youtu.be/-27sHXsvONE>demo video/a>a hrefhttp://roams.caltech.edu/>project/a>/li>/ul>/details>br>b>AI for Science/b>: study how AI methods can improve workflows in science and accelerate knowledge discovery; develop methods for automated experiment design and human-intelligible modeling; deploy in real systems.details>summary>i>b>Selected Publications/b>/i>/summary>ul>li classwide>b>A Foundation Model for Cell Segmentation/b>br>Uriah Israel, Markus Marks, Rohit Dilip, Qilin Li, Morgan Sarah Schwartz, Elora Pradhan, Edward Pao, Shenyi Li, Alexander Pearson-Goulart, Pietro Perona, Georgia Gkioxari, Ross Barnowski, Yisong Yue, David Ashley Van Valenbr>a hrefhttps://www.biorxiv.org/content/10.1101/2023.11.17.567630>bioRxiv/a>a hrefhttps://cellsam.deepcell.org/>service/a>/li>li classwide>b>Self-Supervised Keypoint Discovery in Behavioral Videos/b>br>Jennifer J. Sun*, Serim Ryou*, Roni Goldshmid, Brandon Weissbourd, John Dabiri, David J. Anderson, Ann Kennedy, Yisong Yue, Pietro Peronabr>i>IEEE Conference on Computer Vision and Pattern Recognition (CVPR)/i>, June 2022.br>a hrefhttps://arxiv.org/abs/2112.05121>arxiv/a>/li>li classwide>b>DeepGEM: Generalized Expectation-Maximization for Blind Inversion/b>br>Angela Gao, Jorge Castellanos, Yisong Yue, Zachary Ross, Katherine Boumanbr>i>Neural Information Processing Systems (NeurIPS)/i>, December 2021.br>a hrefpublications/neurips2021_deepgem.pdf>pdf/a>a hrefhttps://github.com/angelafgao/DeepGEM>code/a>a hrefhttp://imaging.cms.caltech.edu/deepgem/>project/a>/li>li classswide>b>End-to-End Sequential Sampling and Reconstruction for MR Imaging/b>br>Tianwei Yin*, Zihui Wu*, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Boumanbr>i>Machine Learning for Health (ML4H)/i>, December 2021.br>font classaward>(Best Paper Award)/font>br>a hrefhttps://arxiv.org/abs/2105.06460>arxiv/a>a hrefhttp://imaging.cms.caltech.edu/seq-mri/>project/a>/li>li classwide>b>Task Programming: Learning Data Efficient Behavior Representations/b>br>Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Yue, Pietro Peronabr>i>IEEE Conference on Computer Vision and Pattern Recognition (CVPR)/i>, June 2021.br>font classaward>(Best Student Paper Award)/font>br>a hrefhttps://arxiv.org/abs/2011.13917>arxiv/a>a hrefhttps://github.com/neuroethology/TREBA>code/a>a hrefhttps://sites.google.com/view/task-programming>project/a>/li>/ul>/details>br>b>Core AI/ML Research/b>: study the underlying fundamental questions pertaining practical algorithm design, inspired by real-world applications in science and engineering. details>summary>i>b>Selected Publications/b>/i>/summary>ul>li classwide>b>Online Policy Optimization in Unknown Nonlinear Systems/b>br>Yiheng Lin, James A. Preiss, Fengze Xie, Emile Anand, Soon-Jo Chung, Yisong Yue, Adam Wiermanbr>i>Conference on Learning Theory (COLT)/i>, 2024br>a hrefhttps://arxiv.org/abs/2404.13009>arxiv/a>/li>li classwide>b>TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis/b>br>Sabera Talukder, Yisong Yue, Georgia Gkioxaribr>a hrefhttps://arxiv.org/abs/2402.16412>arxiv/a>a hrefhttps://github.com/SaberaTalukder/TOTEM>code/a>/li>li classwide>b>Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion/b>br>Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli S Sastry, Siddharth Gururani, Sageev Oore, Yisong Yuebr>i>International Conference on Machine Learning (ICML)/i>, 2024br>a hrefhttps://arxiv.org/abs/2402.14285>arxiv/a>a hrefhttps://scg-rule-guided-music.github.io/>website/a>/li>li classwide>b>Automatic Gradient Descent: Deep Learning without Hyperparameters/b>br>Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan, Yisong Yuebr>a hrefhttps://arxiv.org/abs/2304.05187>arxiv/a>a hrefhttps://github.com/jxbz/agd>code/a>a hrefhttps://towardsdatascience.com/train-imagenet-without-hyperparameters-with-automatic-gradient-descent-31df80a4d249>blog post/a>/li>li classwide>b>LyaNet: A Lyapunov Framework for Training Neural ODEs/b>br>Ivan Dario Jimenez Rodriguez, Aaron D. Ames, Yisong Yuebr>i>International Conference on Machine Learning (ICML)/i>, July 2022.br>a hrefhttps://arxiv.org/abs/2202.02526>arxiv/a>a hrefhttps://github.com/ivandariojr/LyapunovLearning>code/a>/li>li classwide>b>Neurosymbolic Programming/b>br>Swarat Chaudhuri, Kevin Ellis, Oleksandr Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yuebr>i>Foundations and Trends in Programming Languages/i>, Volume 7: No. 3, pages 158-243, December 2021.br>a href/publications/neurosymbolic_preprint.pdf>preprint/a>a hrefhttp://dx.doi.org/10.1561/2500000049>online/a>/li>li classwide>b>Batch Policy Learning under Constraints/b>br>Hoang M. Le, Cameron Voloshin, Yisong Yuebr>i>International Conference on Machine Learning (ICML)/i>, June 2019.br>font classaward>(Oral Presentation)/font>br>a href/publications/icml2019_constrained_batch_learning.pdf>pdf/a>a hrefhttps://arxiv.org/abs/1903.08738>arxiv/a>a hrefhttps://sites.google.com/view/constrained-batch-policy-learn/>project/a>/li>li classwide>b>Multi-dueling Bandits with Dependent Arms/b>br>Yanan Sui, Vincent Zhuang, Joel Burdick, Yisong Yuebr>i>Conference on Uncertainty in Artificial Intelligence (UAI)/i>, August 2017.br>a hrefpublications/uai2017_multi_dueling.pdf>pdf/a>a hrefhttps://arxiv.org/abs/1705.00253>arxiv/a>/li>/ul>/details> div classreadmore> a classnavbar hrefresearch.php#publications>more publications >/a> /div>/div>div classitem>div classtitle>News & Announcements/div>ul>li>b>Humanlike Bot Behavior/b> -- we developed an approach forgenerating humanlike bot behavior from demonstrations, demoed in a gym environment within the Fortnite game engine. a hrefhttps://alexfarhang.github.io/humanlikebehavior>project/a>ahrefhttps://ieeexplore.ieee.org/abstract/document/10645651/>paper/a>br>video srcimages/HumanlikeBehaviorVidCustom.mp4 classimg-fluid roundedz-depth-1 autoplay controls width500>/video>/li>li>b>Farewell!/b> We had five members depart the group during the 2023-2024Academic Year:ul>li>a hrefhttps://ganlumomo.github.io/>Lu Gan/a> completed her postdoc and has started as a faculty at Georgia Tech./li>li>a hrefhttps://acbull.github.io/>Ziniu Hu/a> completed his postdoc and has started at xAI./li>li>a hrefhttps://yjhuangcd.github.io/>Yujia Huang/a> completed her Ph.D. and has started at Citadel Securities./li>li>a hrefhttps://www.jamespreiss.com/>James Preiss/a> completed his postdoc and has started as a faculty at UC Santa Barbara./li>li>a hrefhttps://yangky11.github.io/>Kaiyu Yang/a> completed his postdoc and has started at Meta AI./li>/ul>img srcimages/graduates_2024.jpg width675/>/li>li>b>SceneCraft: An LLM Agent for Synthesizing 3D Scene as Blender Code/b>-- we developed a Large Language Model (LLM) Agent for converting textdescriptions into Blender-executable Python scripts which render complexscenes with up to a hundred 3D assets. This process requires complex spatialplanning and arrangemet, which we tackle through a combination ofadvanced abstraction, strategic planning, and library learning.a hrefhttps://arxiv.org/abs/2403.01248>arxiv/a>br>img srcimages/scenecraft.jpg width650 />/li>li>b>Tokenized Time Series Embeddings/b> -- we developed a framework forlearning a tokenization for downstream time series modeling, includingtraining generalist models that can be applied to many domains. a hrefhttps://arxiv.org/abs/2402.16412>arxiv/a>ahrefhttps://github.com/SaberaTalukder/TOTEM>code/a>br>img srcimages/totem.jpg width650/>/li>li>b>Symbolic Music Generation with Non-Differentiable Rule GuidedDiffusion/b> -- we developed a method for guided diffusion usingnon-differentiable rules, called Stochastic Control Guidance. Our approach isinspired by path integral control and can be applied in a plug-and-play way toany diffusion model. We demonstrate our approach on symbolic musicgeneration.a hrefhttps://arxiv.org/abs/2402.14285>arxiv/a>ahrefhttps://scg-rule-guided-music.github.io/>website/a> br>img srcimages/scg_music.jpg width336 />iframe width336 height189 srchttps://www.youtube.com/embed/HZoQj2FSal4?sieyhE8ciCyHHEBhgp titleYouTube video player frameborder0 allowaccelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share allowfullscreen>/iframe>iframe width336 height189 srchttps://www.youtube.com/embed/gi_RTpghAYs?siHY4i9j1AYK7W6YF6 titleYouTube video player frameborder0 allowaccelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share allowfullscreen>/iframe>iframe width336 height189 srchttps://www.youtube.com/embed/wxgH1LXXh1E?siIILnBjfQYrbanbqS titleYouTube video player frameborder0 allowaccelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share allowfullscreen>/iframe>/li>li>b>SustainGym/b>: we have released a suite of environments designed totest the performance of RL algorithms on realistic sustainability tasks. a hrefhttps://chrisyeh96.github.io/sustaingym/>project/a>a hrefhttps://github.com/chrisyeh96/sustaingym/>code/a>/li>li>b>Farewell!/b> We had three members depart the group during the2022-2023 Academic Year:ul>li>a hrefhttps://jenjsun.com/>Jennifer Sun/a> completed her Ph.D. and willstart as an Assistant Professor at Cornell./li>li>a hrefhttps://www.clvoloshin.com/>Cameron Voloshin/a> completed hisPh.D. and has started at Latitude AI./li>li>a hrefhttps://vdorbs.github.io/>Victor Dorobantu/a> completed his Ph.D. andhas started a postdoc at MIT./li>/ul>img srcimages/2023_grad.jpg width500/>/li>li classwide>b>ICLR 2024/b>: I will be serving as the Senior Program Chair at a hrefhttps://iclr.cc/>ICLR 2024/a>. The rest of Program Chair team includes a hrefhttps://www.cs.utexas.edu/~swarat/>Swarat Chaudhuri/a>, a hrefhttps://www.cs.cmu.edu/~katef/>Katerina Fragkiadaki/a>, a hrefhttps://emtiyaz.github.io/>Emtiyaz Khan/a>, and a hrefhttps://web.cs.ucla.edu/~yzsun/>Yizhou Sun/a>.br>img srchttps://iclr.cc/static/core/img/ICLR-logo.svg />/li>li classwide>b>Automatic Gradient Descent/b>: We have developed a newhyperparameter-free optimizer for deep neural networks. Our method has beendemonstrated at ImageNet scale using ResNet50 architectures. br>a hrefhttps://arxiv.org/abs/2304.05187>arxiv/a>ahrefhttps://github.com/jxbz/agd>code/a>a hrefhttps://towardsdatascience.com/train-imagenet-without-hyperparameters-with-automatic-gradient-descent-31df80a4d249>blog post/a>/li>li classwide>b>Conformal Generative Modeling/b>: We have developed a new framework forgenerative modeling that works on a wide range of manifolds. ahrefhttps://vdorbs.github.io/conformal-generative-modeling>project/a>br>img src/images/conformal_generative_modeling.jpg width650/>/li>/ul>div classreadmore>a classnavbar hrefnews.php>more >/a>/div>/div>div classitem3>center>All Content © 2024 Yisong Yue/center>/div>/div>/div> !-- Start of StatCounter Code --> script typetext/javascript languagejavascript> if(window.location.host www.yisongyue.com) { var sc_project1987806; var sc_invisible1; var sc_partition18; var sc_security396324b8; var script document.createElement(script); script.setAttribute(src, http://www.statcounter.com/counter/counter.js); document.getElementsByTagName(body)0.appendChild(script); } /script> !-- End of StatCounter Code -->/body>/html>
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