The form below is for abstracts intended to be approved for public release only (unclassified with no CUI or other sensitivities). If you would like to present a talk carrying sensitivities, please Contact Us. For those who wish to present more than once during the workshop, please fill out separate abstract submissions per presentation.Company/Organization(Required)Argonne National LaboratoryIdaho National LaboratoryLawrence Livermore National LaboratoryLos Alamos National LaboratoryFlorida State UniversityNew Mexico TechNorth Carolina State UniversityPacific Northwest National LaboratoryPurdue UniversitySandia National LaboratoriesThomas Jefferson National Accelerator FacilityThunderbolt Global AnalyticsUniversity of Nebraska – LincolnUniversity of California, BerkeleyUniversity of California, IrvineUniversity of Colorado BoulderUniversity of New MexicoUniversity of Tennessee KnoxvilleUniversity of Texas at AustinOtherOther Company/Organization Name(Required) Job Title/Role(Required) Presenter Name(Required) First Last Email(Required) Phone(Required)Session Area(s) for Consideration(Required) Applications (e.g., pathing, remote sensing, power systems, etc.) Deep learning (e.g., architectures, generative models, optimization for deep networks, foundation models, LLMs) Probabilistic methods (e.g., variational inference, causal inference, Gaussian processes) Infrastructure (e.g., libraries, improved implementation and scalability, distributed solutions) Scientific machine learning (e.g., physics-informed training, physics-based models, PDEs/ODEs) Reinforcement learning (e.g., decision and control, planning, hierarchical RL, robotics) Theory (e.g., control theory, learning theory, algorithmic game theory) Generative AI (e.g., large language models, diffusion models, transformers) Trustworthy Machine Learning (e.g., accountability, causality, fairness, privacy, robustness) OTHER (does not fit into other categories) Presentation Title(Required) Abstract(Required)Please provide your presentation abstract for committee review. The abstract is limited to roughly 500 words (3000 characters). SAND Number(Required) Please acknowledge that the material you are submitting is unclassified with no sensitivities.(Required)If your presentation materials are other than UUR please reach out to the appropriate lead. I acknowledge that materials are unclassified and appropriate for public release. Estimated Length of PresentationThis timeframe DOES NOT include Q&A time. 15 minutes 20 minutes 30 minutes CAPTCHAEmailThis field is for validation purposes and should be left unchanged.
