ALL NPPS Members

[Torre Wenaus <wenaus AT gmail.com>]

Re-sending with attachments removed. Note sympa bounces mails with trivially small attachments, the size limit is way low. We're trying to get it fixed.

On Tue, Oct 22, 2024 at 3:41 PM Torre Wenaus <wenaus AT gmail.com> wrote:

This is right when our group lunch is scheduled, and this looks worth attending. 

So another bump for the lunch! I propose a Halloween lunch, Oct 31 noon departure. You can reply just to me whether that works for you.

  Torre

---------- Forwarded message ---------
From: Medaglia, Nicole <medaglia AT bnl.gov>
Date: Tue, Oct 22, 2024 at 3:32 PM
Subject: Brookhaven AI/ML Seminar (AIMS): Ruben Ohana and Michael McCabe, Flatiron Institute, New York, Tuesday, October 29th at 12PM ET
To: CDS Directorate <CDSDirectorate AT bnl.gov>, Physics Personnel <PhysicsPersonnel AT bnl.gov>, CDSStudents2024 <CSIStudents2024 AT brookhavenlab.onmicrosoft.com>, CFN Staff (Group) <allnanomaterials AT bnl.gov>, CMPMSD <cmpmsd AT bnl.gov>, Environmental & Climate Sciences Dept <eslist AT bnl.gov>, CO Scientific Staff <coscistf AT bnl.gov>, NSLS-II Personnel <allPhotonSciences AT bnl.gov>, Energy Sciences Directorate <EnergySciencesDirectorate AT bnl.gov>, EBNN Directorate <EBNNDirectorate AT bnl.gov>, Instrumentation Personnel <allinstrument AT bnl.gov>, Chemistry Personnel <allchemistry AT bnl.gov>, CAD Personnel List <allcad AT bnl.gov>, aiml-wg-l AT lists.bnl.gov <aiml-wg-l AT lists.bnl.gov>, ankitanarendra.nagpal AT stonybrook.edu <ankitanarendra.nagpal AT stonybrook.edu>
Cc: Ruben Ohana <rohana AT flatironinstitute.org>, Michael McCabe <mmccabe AT flatironinstitute.org>

Brookhaven AI/ML Seminar (AIMS)

Time/Date: 12:00 PM ET, Tuesday, October 29th, 2024

Location: Building 725 Training Room and Virtual ZOOM (linked below) 

Title: Building foundation models for scientific data 

Seminar Speaker: Ruben Ohana, Ph.D. and Michael McCabe, Ph.D - Flatiron Institute, New York

 

Abstract: Foundation models are very large architectures trained on large-scale datasets and can be used to transfer knowledge from a domain to another. Scientific data, particularly numerical simulations of partial differential equations (PDEs), presents unique challenges due to its complexity and the need for domain expertise to assess prediction quality, complicating the building of the first foundation models in this field. In this talk, we will develop our approach of building foundation models for scientific data, highlighting the requirements and expectations for achieving meaningful results. We will also introduce The Well, a comprehensive collection of datasets encompassing multi-scale simulations of fluid dynamics, astrophysics, and biological systems. The Well serves as a foundation for developing models that generalize across diverse physical phenomena, aiming to accelerate scientific discovery through large-scale learning.

­­­­­_____________________________________________________________________

 

Topic: Brookhaven AI/ML Seminar (AIMS): Ruben Ohana and Michael McCabe, Flatiron Institute, New York, Tuesday, October 29th at 12PM ET

Time: Oct 29, 2024 12:00 PM Eastern Time (US and Canada)

 

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Meeting ID: 160 689 8802

Passcode: 281575

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--

-- Torre Wenaus, BNL NPPS Group, ATLAS Experiment

-- BNL 510A 1-222 | 631-681-7892

--

-- Torre Wenaus, BNL NPPS Group, ATLAS Experiment

-- BNL 510A 1-222 | 631-681-7892