I am a research scientist at Google Research. Previously I was a postdoctoral researcher at Empirical Inference Department, Max Planck Institute for Intelligent Systems working with Bernhard Schölkopf (from 2018 to 2020). I work in the field of machine learning (intersection of computer science and statistics). My research topics include (but not limited to)

  • Fast (linear runtime) non-parametric statistical tests
  • Kernel-based representation of data
  • Deep generative modelling of images
  • Approximate Bayesian inference
I completed my PhD study in 2017 at Gatsby Unit, UCL where I worked with Arthur Gretton on various topics related to kernel-based statistical tests and approximate Bayesian inference. Please feel free to check out my list of publications, software and contact me for a research discussion.

Contact: Wittawat Jitkrittum (วิทวัส จิตกฤตธรรม) ( )

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Last update: 03-Jul-24
Based on al-folio theme.

News

1 May 2024

:memo: “USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval” has been accepted to ICML 2024.
16 Jan 2024

:memo::memo: :memo: :memo: Four papers accepted to ICLR 2024.
11 Dec 2023

:bullettrain_front: At NeurIPS 2023 presenting our paper “When Does Confidence-Based Cascade Deferral Suffice?”