• Cornell colloquium

    Drexel Colloquium 4/2024

  • principle of urban science V

    machine learning | data ethics

  • LSDSS 2024 time series analysis

    Autoencoders and RNNs

  • LSDSS 2024: Manifold Learning and Autoencoders

  • LSDSS 2024: intro to DS

  • ANN101

  • Fermi summer school 24

    Fermi summer school 24

  • m3

  • needles in rubin haystacks

  • Drexel colloquium

    Drexel Colloquium 4/2024

  • RAS MMA GW

    KN perspective detection with the Vera C. Rubin Observatory

  • FEET24

    KN perspective detection with the Vera C. Rubin Observatory

  • DSI meeting lightening talk

  • SOLAR NEIGHBORHOOD ULTRACOOL DWARFS

  • Data Science for Everyone - ethics

    generative AI

  • Foundations of Data Science for Everyone 13

    generative AI

  • Data Science for (Physical) scientists

    PINNs and generative AI

  • data science for (physical) scientists 13

    convolutional neural networks

  • Foundations of Data Science for Everyone

    CNNs

  • Fundations of Dta Science for Everyone

    neural networks

  • Data Science for Physical Scientists

    some notes on visualizations

  • Foundations of Data Science for Everyone

    some notes on visualizations

  • data sciencefor (physical) scientists 9

    clustering

  • MAS APS 2023 astronomy + AI

  • data science for (physical) scientists 8

    distances, knn, intro to clustering

  • data science for (physical) scientists VII

    MCMC

  • Foundations of Data Science for Everyone - IX : Clustering

  • Nurturing the future generations of Rubin scientists with effective, culturally responsive mentoring

  • Surveys23/WFIS 2023

  • Gravi-Gamma-Nu 2023

  • NSF AAAC 2023

  • LSST surgey strategy

    CSU-LCO Student Data Workshop

  • VIZ metals23

    some notes on visualizations

  • METAL23

  • dsu23_1

  • StraussLuptonFest

  • Copy of MLTSA11 2022

    transformers

  • machine learning for natural and physical scientists 2023 10

    autoencoders

  • Machine learning for natural and physical scientists 2023 8

    DNN 101 - deepdreams

  • machine learning for natural and physical scientists 2023 5

    k-NN and CARTS

  • machine learning for natural and physical scientists 2023 4

    clustering

  • machine learning for natural and physical scientists 2023 3

    intro to time series and regression

  • machine learning for natural and physical scientists 2 (2023)

    probability and statistics

  • UD 2023 Physics 838 SN Cosmology

  • machine learning for natural and physical scientists 1, 2023

    intro to this class

  • Kahn symposium

  • UMD seminar

    UMD Colloquium Rubin LSST 2/2023

  • FDSfA 9

    NLP

  • CIERA jc

    NorthWestern Colloquium Rubin LSST 11/2022

  • CIERA seminar

    NorthWestern Colloquium Rubin LSST 11/2022