Scholar
Timur Garipov
Google Scholar ID: gWQzBQMAAAAJ
OpenAI
Citations & Impact
Citations
5,518
H-index
10
i10-index
11
Publications
19
Co-authors
35
list available
Contact
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- - Conference papers:
- - Compositional Sculpting of Iterative Generative Processes, NeurIPS 2023
- - Adversarial Support Alignment, ICLR 2022
- - Subspace inference for Bayesian deep learning, UAI 2019
- - A Simple Baseline for Bayesian Uncertainty in Deep Learning, NeurIPS 2019
- - Averaging Weights Leads to Wider Optima and Better Generalization, UAI 2018
- - Defended his PhD thesis: 'Guiding Deep Probabilistic Models'
Research Experience
- - Researcher at OpenAI
- - Completed a research internship at Google Brain in the summer of 2021, working with Chiyuan Zhang
- - Completed an internship at Cruise AI Research team in the summer of 2023, supervised by David Hayden
Education
- - PhD in Computer Science, MIT EECS & MIT CSAIL, advised by Tommi Jaakkola
- - BSc and MSc in Applied Mathematics and Computer Science, Lomonosov Moscow State University, supervised by Dmitry Vetrov
Background
- Research interests: probabilistic machine learning and deep learning, with a focus on LLM reasoning, generative models, empirical approaches to understanding training, robustness, and generalization of deep neural networks.
Miscellany
- Personal website includes links to Google Scholar, Twitter, and GitHub
