Slides

Sam Foreman

Recent Talks

Large Scale Training, at Introduction to AI-driven Science on Supercomputers: A Student Training Series, November 2022 </p> <p> <p>Your browser does not support iframes.</p> </p>
Hyperparameter Management, at 2022 ALCF Simulation, Data, and Learning Workshop, October 2022 </p> <p> <p>Your browser does not support iframes.</p> </p>
Statistical Learning, at ATPESC 2022, August 2022 📕 accompanying notebook </p> <p> <p>Your browser does not support iframes.</p> </p>
Scientific Data Science: An Emerging Symbiosis, at Argonne National Laboratory, May 2022 </p> <p> <p>Your browser does not support iframes.</p> </p>
Machine Learning in HEP, at UNC Greensboro, March 2022 </p> <p> <p>Your browser does not support iframes.</p> </p>
Accelerated Sampling Methods for Lattice Gauge Theory, at BNL-HET & RBRC Joint Workshop “DWQ @ 25”, Dec 2021 </p> <p> <p>Your browser does not support iframes.</p> </p>
Training Topological Samplers for Lattice Gauge Theory, ML4HEP, on and off the Lattice @ ECT* Trento, Sep 2021 </p> <p> <p>Your browser does not support iframes.</p> </p>
l2hmc-qcd at the MIT Lattice Group Seminar, 2021
Deep Learning HMC for Improved Gauge Generation to the Machine Learning Techniques in Lattice QCD Workshop, 2021
Machine Learning for Lattice QCD at the University of Iowa, 2020 </p> <p> <p>Your browser does not support iframes.</p> </p>
Machine learning inspired analysis of the Ising model transition to Lattice, 2018
Machine Learning Analysis of Ising Worms at Brookhaven National Laboratory, 2017

Citation

BibTeX citation:

@online{foreman,
  author = {Foreman, Sam},
  title = {Slides},
  url = {https://87ceaf89-db22-41c3-aef1-dd7e61e39a82.netlify.app//content/slides.html},
  langid = {en}
}

For attribution, please cite this work as:

Foreman, Sam. n.d. “Slides.” https://87ceaf89-db22-41c3-aef1-dd7e61e39a82.netlify.app//content/slides.html.

--- title: "Slides" title-block-style: none date-modified: 2023-05-12 --- # Recent Talks - [**Large Scale Training**](https://saforem2.github.io/ai4sci-large-scale-training), at [Introduction to AI-driven Science on Supercomputers: A Student Training Series](https://github.com/argonne-lcf/ai-science-training-series), November 2022 <iframe src="https://saforem2.github.io/ai4sci-large-scale-training/#" title="Large Scale Training" width="66%" align="center" height="400" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="margin-top:1em;margin-bottom:1em;border:none;align:center;"> <p>Your browser does not support iframes.</p> </iframe> - [**Hyperparameter Management**](https://saforem2.github.io/hparam-management-sdl2022/), at [2022 ALCF Simulation, Data, and Learning Workshop](https://www.alcf.anl.gov/events/2022-alcf-simulation-data-and-learning-workshop), October 2022 <iframe src="https://saforem2.github.io/hparam-management-sdl2022" title="Hyperparameter Management" width="66%" align="center" height="400" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="margin-top:1em;margin-bottom:1em;border:none;align:center;"> <p>Your browser does not support iframes.</p> </iframe> - [**Statistical Learning**](https://saforem2.github.io/ATPESC-StatisticalLearning), at [ATPESC 2022](https://extremecomputingtraining.anl.gov/), August 2022 [📕 accompanying notebook](https://github.com/argonne-lcf/ATPESC_MachineLearning/blob/master/00_statisticalLearning/src/atpesc/notebooks/statistical_learning.ipynb) <iframe src="https://saforem2.github.io/ATPESC-StatisticalLearning/#/" title="Statistical Learning" width="66%" align="center" height="400" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="margin-top:1em;margin-bottom:1em;border:none;align:center;"> <p>Your browser does not support iframes.</p> </iframe> - [**Scientific Data Science: An Emerging Symbiosis**](https://saforem2.github.io/anl-job-talk/), at Argonne National Laboratory, May 2022 <iframe src="https://saforem2.github.io/anl-job-talk" title="Scientific Data Science" width="66%" align="center" height="400" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="margin-top:1em;margin-bottom:1em;border:none;align:center;"> <p>Your browser does not support iframes.</p> </iframe> - [**Machine Learning in HEP**](https://saforem2.github.io/physicsSeminar), at UNC Greensboro, March 2022 <iframe src="https://saforem2.github.io/physicsSeminar" title="Machine Learning in HEP" width="66%" align="center" height="300" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="border:none;margin-top:1em;margin-bottom:1em;"> <p>Your browser does not support iframes.</p> </iframe> - [**Accelerated Sampling Methods for Lattice Gauge Theory**](https://saforem2.github.io/l2hmc-dwq25/), at [_BNL-HET & RBRC Joint Workshop "DWQ @ 25"_](https://indico.bnl.gov/event/13576/), Dec 2021 <iframe src="https://saforem2.github.io/l2hmc-dwq25" title="Accelerated Sampling Methods for Lattice Gauge Theory" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen width="66%" align="center" height="400" style="border:none;margin-top:1em;margin-bottom:1em;"> <p>Your browser does not support iframes.</p> </iframe> - [**Training Topological Samplers for Lattice Gauge Theory**](https://saforem2.github.io/l2hmc_talk_ect2021/), [_ML4HEP, on and off the Lattice_](https://indico.ectstar.eu/event/77/contributions/2349/) @ ECT\* Trento, Sep 2021 <iframe src="https://saforem2.github.io/l2hmc_talk_ect2021" title="Training Topological Samplers for Lattice Gauge Theory" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen width="66%" align="center" height="400" style="border:none;margin-top:1em;margin-bottom:1em;"> <p>Your browser does not support iframes.</p> </iframe> - [**l2hmc-qcd**](https://github.com/saforem2/l2hmc-qcd) at the _MIT Lattice Group Seminar_, 2021 - [**Deep Learning HMC for Improved Gauge Generation**](https://bit.ly/mainz21) to the [_Machine Learning Techniques in Lattice QCD Workshop_](https://bit.ly/mainz21_overview), 2021 - [**Machine Learning for Lattice QCD**](https://slides.com/samforeman/l2hmc-qcd-93bc0c) at the University of Iowa, 2020 <iframe src="https://slides.com/samforeman/l2hmc-qcd/embed" title="Machine Learning for Lattice QCD" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen width="66%" align="center" height="400" style="border:none;margin-top:1em;margin-bottom:1em;"> <p>Your browser does not support iframes.</p> </iframe> - [**Machine learning inspired analysis of the Ising model transition**](https://bit.ly/latt2018) to [_Lattice, 2018_](https://indico.fnal.gov/event/15949/overview) - **Machine Learning Analysis of Ising Worms** at _Brookhaven National Laboratory_, 2017