ServiceNow Research

Pierre-André Noël

Pierre-André Noël

Applied Research Scientist

Low Data Learning

Pierre-André Noël is an Applied Research Scientist at ServiceNow Research. His recent work involves Graph Neural Networks, Self-Supervised Learning, Relational Databases, Knowledge Graphs and/or Constrained Inference. He holds a PhD in Physics from Université Laval and was a postdoctoral researcher at University of California Davis. His doctoral and postdoctoral research pertained to Complex Networks, Statistical Mechanics and Stochastic Processes. In 2017, he joined an NLP team at Element AI where he spent the following years building core capabilities and working on special projects. ServiceNow acquired Element AI in 2021, and Pierre-André now focuses on fundamental research, with an applied twist.

Interests
  • Relational Models
  • Diffusion Models
  • Generative Models
  • Theory of Machine Learning

Publications

Exploring the Design Space of Generative Diffusion Processes for Sparse Graphs. Workshop at the Neural Information Processing Systems (NeurIPS),  2022.

Cite

On the Value of ML Models. Workshop at the Neural Information Processing Systems (NeurIPS),  2021.

PDF Cite