René's URL Explorer Experiment


Title: Welcome! - Max Simchowitz

Open Graph Title: Welcome!

Mail addresses
msimchow (at) andrew.cmu.edu

Opengraph URL: https://msimchowitz.github.io/

direct link

Domain: msimchowitz.github.io


Hey, it has json ld scripts:
 { "@context" : "http://schema.org", "@type" : "Person", "name" : "Max Simchowitz", "url" : "https://msimchowitz.github.io", "sameAs" : null } 

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og:site_nameMax Simchowitz
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theme-color#ffffff

Links:

Max Simchowitzhttps://msimchowitz.github.io/
Publicationshttps://msimchowitz.github.io/publications/
Peoplehttps://msimchowitz.github.io/people/
Talkshttps://msimchowitz.github.io/talks/
Teachinghttps://msimchowitz.github.io/teaching/
Bloghttps://muchnoise.substack.com/
Carnegie Mellon Universityhttps://www.ml.cmu.edu/
CVhttps://msimchowitz.github.io/files/maxs_cv.pdf
Google Scholarhttps://scholar.google.com/citations?user=HjmSOFEAAAAJ&hl=en
Githubhttps://github.com/msimchowitz
Substackhttps://muchnoise.substack.com
X (formerly Twitter)https://twitter.com/max_simchowitz
ORCIDhttps://orcid.org/0000-0001-9900-1238
Why do today’s robotic policies work so well, and how can we make them betterhttps://simchowitzlabpublic.github.io/much-ado-about-noising-project/
Machine Learning Departmenthttps://ml.cmu.edu
Robotics Institutehttps://ri.cmu.edu
Action Chunking and Exploratory Data Collection Yield Exponential Improvements in Behavior Cloning for Continuous Controlhttps://arxiv.org/abs/2507.09061
Much Ado About Noising: Dispelling the Myths of Generative Robotic Controlhttps://simchowitzlabpublic.github.io/much-ado-about-noising-project/
The Pitfalls of Imitation Learning when Actions are Continuoushttps://arxiv.org/abs/2503.09722
Diffusion Policy Policy Optimizationhttps://diffusion-ppo.github.io/
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusionhttps://boyuan.space/diffusion-forcing/
Do Differentiable Simulators Give Better Policy Gradients?https://arxiv.org/pdf/2202.00817.pdf
Naive Exploration is Optimal for Online LQRhttps://arxiv.org/abs/2001.09576
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identificationhttps://arxiv.org/pdf/1802.08334
Constrained Bimanual Planning with Analytic Inverse Kinematicshttp://arxiv.org/abs/1507.03566
Constrained Bimanual Planning with Analytic Inverse Kinematicshttps://arxiv.org/abs/2305.06341
Do Differentiable Simulators Give Better Policy Gradients?https://arxiv.org/pdf/2202.00817
Delayed Impact of Fair Machine Learninghttps://arxiv.org/abs/1803.04383
https://msimchowitz.github.io/
https://msimchowitz.github.io/
Sanjeev Arorahttps://www.cs.princeton.edu/~arora/
David Bleihttp://www.cs.columbia.edu/~blei/">
Ben Rechthttp://www.eecs.berkeley.edu/~brecht
Michael Jordanhttp://www.cs.berkeley.edu/~jordan/
Elad Hazanhttps://ehazan.com/
Kevin Jamiesonhttps://homes.cs.washington.edu/~jamieson/about.html
Robot Locomotion Grouphttps://locomotion.csail.mit.edu/people.html
EECS Departmenthttps://www.eecs.mit.edu
Sitemaphttps://msimchowitz.github.io/sitemap/
GitHubhttp://github.com/msimchowitz
Feedhttps://msimchowitz.github.io/feed.xml
Jekyllhttp://jekyllrb.com
AcademicPageshttps://github.com/academicpages/academicpages.github.io
Minimal Mistakeshttps://mademistakes.com/work/minimal-mistakes-jekyll-theme/

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