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Unlocking the Power of Large Language Models for Research Innovation
Online Presentations | 21 May 2024 | Contributor(s):: Juan Carlos Verduzco Gastelum
In this hands-on workshop, Dr. Juan C. Verduzco will showcase the transformative potential of large language models (LLMs) and their applications to research tasks. First, this presentation explores the essential building blocks of LLMs, such as embeddings, attention mechanisms, and transformer...
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Introduction to Programming with LLM Coding Assistants
Online Presentations | 09 May 2024 | Contributor(s):: Kat Nykiel
This MNT-CURN workshop will introduce students to the use of large language models (LLMs) as coding assistants.
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Workshop: Large Language Models as Coding Assistants
Tools | 12 Apr 2024 | Contributor(s):: Kat Nykiel
This workshop will teach students how to use large language models as coding assistants through web-based chatbots and editor-integrated chatbots
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Data-Driven Materials Innovation: where Machine Learning Meets Physics
Online Presentations | 29 Nov 2023 | Contributor(s):: Anand Chandrasekaran
Learn how Schrödinger’s tools can address common issues by using a combination of physics-based simulation data, enterprise informatics, and chemistry-aware ML.
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Hands-On Workshop in nanoHUB: Machine Learning Models for Ionic Conductivity with Schrödinger's AutoQSAR
Online Presentations | 29 Nov 2023 | Contributor(s):: Michael Rauch
In this workshop, we will demonstrate the hands-on use of Schrödinger's MS Maestro graphical user interface within nanoHUB to perform machine learning model creation and implementation.
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SCALE AI and Radiation Effects
Online Presentations | 18 Oct 2023 | Contributor(s):: Michael Alles
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Machine Learning in Materials Science: Image Analysis Using Convolutional Neural Networks in MatCNN
Courses | 03 Nov 2021 | Contributor(s):: Tiberiu Stan, Jim James, Nathan Pruyne, Marcus Schwarting, Jiwon Yeom, Peter Voorhees, Ben J Blaiszik, Ian Foster, Jonathan D Emery
This course introduces fundamental concepts of artificial intelligence within the context of materials science and image segmentation. The two-week module was taught as part of a Computational Methods in Materials Science course at Northwestern University. The module is aimed at...
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FDNS21: Autonomous Research Systems for Carbon Nanotube Synthesis
Online Presentations | 20 May 2021 | Contributor(s):: Benji Maruyama
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Advancing Photonic Device Design and Quantum Measurements with Machine Learning
Online Presentations | 18 Dec 2020 | Contributor(s):: Alexandra Boltasseva
In this talk, photonic design approaches and emerging material platforms will be discussed showcasting machine-learning-assisted topology optimization for thermophotovoltaic metasurface designs and machine-learning-enabled quantum optical measurements.
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Perspectives on High-Performance Computing in a Big Data World: Part D - Learning Model Details and Agent-Based Simulations
Online Presentations | 17 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture completes the discussion of MLforHPC. It covers Learning Model Details and Agents and Time-Series Case Studies.
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Perspectives on High-Performance Computing in a Big Data World: Part E - Challenges and Opportunities, Conclusions
Online Presentations | 17 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture covers the computer science issues raised in this talk. The conclusions note that HPDC/HPC is essential; it is good to work closely with industry with student Internships and Collaborations; the Global AI and Modeling Supercomputer GAIMSC is a good framework with an HPC Cloud linked...
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Perspectives on High-Performance Computing in a Big Data World: Part C - MLaroundHPDC/HPC and MLAutotuning
Online Presentations | 10 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This is the first part of the discussion of MLforHPC. It includes MLAutotuning (Using ML to configure or autotune ML or HPC simulations and MLaroundHPC (Learning outputs from inputs).
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Perspectives on High-Performance Computing in a Big Data World
Courses | 30 Sep 2019 | Contributor(s):: Fox, Geoffrey C.
This course was deleivered at ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC).High-Performance Computing (HPC) and Cyberinfrastructure have played a leadership role in computational science even since the start of the NSF computing centers program. Thirty...
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Perspectives on High-Performance Computing in a Big Data World: Part B - More on the Evolution of Interests and Communities
Online Presentations | 30 Sep 2019 | Contributor(s):: Fox, Geoffrey C.
This part contains several topics. It discusses the importance of industry in several facets of the field: SysML conference, clouds, MLPerf, the Global AI Supercomputer. The nature of data science and data engineering jobs. We emphasize the need for HPC. We finish by introducing MLforHPC (AI for...
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Perspectives on High-Performance Computing in a Big Data World: Part A - Data on the Evolution of Interests and Communities
Online Presentations | 13 Aug 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture has an overall outline of the 5 part presentation. It covers trends seen from conferences and journals -- the number of papers, attendees and h5index. Then we look at relevant Google Trends. Cyberinfrastructure related activities are less buoyant than those for AI and ML.
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How do we solve big science problems using all the modern tools and technologies at our fingertips?
Online Presentations | 06 Jul 2019 | Contributor(s):: Jeffrey A. Nichols
Exascale is on the horizon and ORNL just announced our next new system called Frontier to be delivered in 2021 – another order of magnitude more powerful! I will discuss the technologies used in Summit and Frontier.
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Introduction to Deep Reinforcement Learning
Online Presentations | 03 Jul 2019 | Contributor(s):: Balaraman Ravindran
Reinforcement learning is a paradigm that aims to model the trial-and-error learning process that is needed in many problem situations where explicit instructive signals are not available. It has roots in operations research, behavioural psychology and AI. ...
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Human-Interpretable Concept Learning via Information Lattices
Online Presentations | 23 May 2019 | Contributor(s):: Lav R. Varshney
The basic idea is an iterative discovery algorithm that has a student-teacher architecture and that operates on a generalization of Shannon’s information lattice, which itself encodes a hierarchy of abstractions and is algorithmically constructed from group-theoretic foundations.
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Future of AI and Quantum Computing
Online Presentations | 21 Feb 2019 | Contributor(s):: Dario Gil
This presentation will review how IBM’s superconducting qubit implementation and Qiskit software framework is enabling researchers, developers and industrial partners worldwide to explore this new technology.
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Magnetic Tunnel Junction (MTJ) as Stochastic Neurons and Synapses: Stochastic Binary Neural Networks, Bayesian Inferencing, Optimization Problems
Online Presentations | 26 Oct 2018 | Contributor(s):: Abhronil Sengupta, Kaushik Roy
In this presentation, we provide a multi-disciplinary perspective across the stack of devices, circuits, and algorithms to illustrate how the stochastic switching dynamics of spintronic devices in the presence of thermal noise can provide a direct mapping to the units of such computing...