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author=SBM @ NeurIPS ;
description=A workshop to bring together researchers who use score-based methods in machine learning and statistics.;
keywords=score functions, score-based methods, diffusion;

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sbm neurips sbm neurips toggle navigation home current schedule accepted papers call for papers neurips 2022 workshop on score based methods a workshop to bring together researchers who use score based methods in machine learning and statistics click here for registration click here to submit your questions to our panelists introduction the score function which is the gradient of the log density provides a unique way to represent probability distributions by working with distributions through score functions researchers have been able to develop efficient tools for machine learning and statistics collectively known as score based methods score based methods have had a significant impact on vastly disjointed subfields of machine learning and statistics such as generative modeling bayesian inference hypothesis testing control variates and stein s methods for example score based generative models or denoising diffusion models have emerged as the state of the art technique for generating high quality and diverse images in addition recent developments in stein s method and score based approaches for stochastic differential equations sdes have contributed to the developement of fast and robust bayesian posterior inference in high dimensions these have potential applications in engineering fields where they could help improve simulation models at our workshop we will bring together researchers from these various subfields to discuss the success of score based methods and identify common challenges across different research areas we will also explore the potential for applying score based methods to even more real world applications including in computer vision signal processing and computational chemistry by doing so we hope to folster collaboration among researchers and build a more cohesive research community focused on score based methods this workshop will be an in person event at neurips 2022 taking place on dec 2nd 2022 from 8 50am to 5 00pm in room 293 294 at the new orleans convention center the session will cover invited talks contributed talks posters and a panel discussion key dates submission deadline sept 26 2022 11 59 pm aoe acceptance notification oct 20 2022 camera ready for accepted submissions nov 25 2022 keynote speakers chenlin meng stanford university guan horng liu georgia institute of technology karsten kreis nvidia research mohammad norouzi google brain tommi jaakkola mit tamara fernandez adolfo ibañez university panelists aapo hyvärinen university of helsinki arnaud doucet university of oxford deepmind jascha sohl dickstein google brain rianne van den berg microsoft research qiang liu university of texas at austin mark chen openai sander dieleman deepmind organizers yingzhen li imperial college london yang song openai valentin de bortoli cnrs françois xavier briol university college london wenbo gong microsoft research alexia jolicoeur martineau samsung sait ai lab montreal arash vahdat nvidia research contact for any questions please contact us at scorebased workshop gmail com sponsors openai has generously agreed to sponsor around 6 workshop tickets for student from minority groups please fill in the form nvidia has generously provided 2 gpus as gifts for our awardees copyright 2022 sbm neurips powered by jekyll with al folio theme hosted by github pages