2024 MLDL Conference Schedule

Day 3: Wednesday, September 11, 2024

Track 1

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+1 505-373-1510,,486578405# United States, Albuquerque

Track 2

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+1 505-373-1510,,969844935# United States, Albuquerque

Keynote and EOD Q&A

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+1 505-373-1510,,877929334#United States, Albuquerque

Track 1 Q&A

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+1 505-373-1510,,308241642# United States, Albuquerque

Track 2 Q&A

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+1 505-373-1510,,41361731# United States, Albuquerque

Topics: Trusted AI & Tools, Processing and Pipelines for ML

Track 1: Topic - Trusted AI
Time (MST) Title Speaker Media/Materials
9:10 am Keynote: You Should Give a Tutorial Sarah Ackerman (SNL) SAND2024-11426V Video SAND2024-11279C PPTX
9:50 am Trust Maturity Model for AI Systems Scott Steinmetz (SNL) SAND2024-10909O Video SAND2024-09809C PPTX
11:20 am MADmax: Multi-Agent Trust Dynamics and Influence Maximization Asael H. Sorensen (SNL) SAND2024-10692V Video SAND2024-10202PE PDF
11:40 am Zig Zag Persistence as a Measure of Topology Preservation in Temporal Link Prediction Marco Campos (SNL) SAND2024-11759C Video
1:00 pm Keynote: Adjusting for Spatial Correlation in Machine and Deep Learning Matt Heaton (BYU) Video | PPTX
1:40 pm HaMLET: Human and Machine Learning Effective Teaming Kyra Wisniewski (SNL) SAND2024-10160V Video SAND2024-09811C PPTX
2:05 pm Graph attention embeddings as a causal lens in temporal link prediction Sarah Simpson (SNL) SAND2024-10212C Video SAND2024-09855C Video
2:30 pm Trusted AI Lightning Talks from Sandia's LDRD Research Programs Various Speakers (SNL): 1- David Stracuzzi | 2- Mike Smith | 3-Jeremy Wendt | 4 - John Jakeman | 5- Kyle Neal | 6- Carlos Llosa | 7- Alexander Outkin | 8- Kyra Wisniewski | SAND2024-11496V Video1: Defining Trusted AI SAND2024-11468V Video2: Trustworthiness SAND2024-11329C Video3: Distance Learning SAND2024-11656V Video4: CERTANN SAND2024-11076C Video5: Datadriven Closure Models SAND2024-10879V Video6: Tensor Decompositions SAND2024-11950C Video7: Information&PrivacyLoss SAND2024-10849V Video8: Model Trust in AI

Track 2: Topics - Tools, Processing, and Pipelines for Machine Learning
Time (MST) Title Speaker Media/Materials
9:10 am Keynote: You Should Give a Tutorial Sarah Ackerman (SNL) SAND2024-11426V Video SAND2024-11279C PPTX
9:50 am Designing Large Datasets: Data-Scarce and Stable Deep Generative Models for Turning Sparse Experiments into Big Datasets in Materials Science Andreas E. Robertson (SNL) SAND2024-09804O Video SAND2024-09646C PPTX
10:40 am Artificial Intelligence for Microelectronics Security and Trust Prabuddha Chakraborty (UMaine) Video | PDF
11:20 am Arbitrary Autoencoder Injection for Interpretability Experimentation Michael Xi (SNL) SAND2024-11205C Video
11:40 am MatFold: cross-validation protocols to systematically evaluate OOD performance in materials discovery models Matthew Witman (SNL) SAND2024-10214C Video | PPTX
1:00 pm Keynote: Adjusting for Spatial Correlation in Machine and Deep Learning Matt Heaton (BYU) Video | PPTX
1:40 pm CrossSim: Sandia's simulator for analog AI accelerators Patrick Xiao (SNL) SAND2024-10513O Video
2:05 pm Mixed CNN-Attention Machine Learning Model for Predicting Gene Regulatory Relationships Across Fungal Species Towards Developing Computational Methods for Defending Against Emerging Pathogenic Fungi Laura Weinstock (SNL) SAND2024-10546V Video SAND2024-10235PE PPTX
2:30 pm Simplifying ML Pipeline Deployment for the Scientific Community in Different Computing Environments: An Integrated Approach with Clowder, Ray and HuggingFace Vismayak Mohanarajan (National Center for Supercomputing Applications) Video
Track 1: Trusted AI Lightning Talks from Sandia's LDRD Research Programs Various Speakers (SNL)

Day 4: Schedule

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