Thomas X. Wang
  • Bio
  • Papers
  • Teaching
  • Recent & Upcoming Talks
    • Example Talk
  • Publications
    • Zebra: In-Context and Generative Pretraining for Solving Parametric PDEs
    • Weight Conditioning for Smooth Optimization of Neural Networks
    • AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields
    • AutoBasisEncoder: Pre-trained Neural Field Basis via Autoencoding for Operator Learning
    • Operator Learning with Neural Fields: Tackling PDEs on General Geometries
    • Handling unstructured data for operator learning using implicit neural representations
  • Teaching
    • Teaching
    • Learn JavaScript
    • Learn Python
  • Projects
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Experience
  • Teaching
    • Data Science (LU1INMA1)
    • Algorithms (LU2IN003)
    • Data Science (LU1INMA1)
    • Algorithms (LU2IN003)
  • Publications
    • An example preprint / working paper
    • An example journal article
    • An example conference paper
Teaching
Data Science (LU1INMA1)

Data Science (LU1INMA1)

Sep 1, 2023 · 1 min read

Term: Fall 2023
Role: Teaching Assistant
Institution: Sorbonne Université

Last updated on Sep 1, 2023
Thomas X. Wang
Authors
Thomas X. Wang
PhD Student in Deep Learning
Algorithms (LU2IN003) Jan 1, 2023 →

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