GitHub Demos for Machine Learning for Inverse Problems and Data Assimilation
I wrote a detailed GitHub repository of textbook-ready demo notebooks for Machine Learning for Inverse Problems and Data Assimilation.
Jul 8, 2026
Variational Flow Maps: Make Some Noise for One-Step Conditional Generation
Variational Flow Maps (VFM) recasts conditional generation as a problem of learning the right initial noise distribution for a pretrained or jointly trained one-step flow map. An observation-dependent adapter transforms simple noise before the flow map sends it to data space, enforcing the measurement while retaining the learned data prior.
Jul 7, 2026
ILAS 2026 Talk - Learning Enhanced Ensemble Filters: Continuum Limits of Attention on Measures
I will speak at ILAS 2026 on Tuesday, May 19, 2026, 2:50 PM Eastern, in McBryde Hall 113 at Virginia Tech.
May 19, 2026
🔊 Make Some Noise: Variational Flow Maps for One-Step Conditional Generation
Our ICML 2026 paper learns the right initial noise for fast, calibrated conditional generation, inverse problems, and reward alignment.
Mar 10, 2026
Talk Announcement: SIAM Student Chapter Talk - Learnable Operators on Probability Measures for Ensemble Data Assimilation
I will give a SIAM student chapter talk on Wednesday, March 11, 2026, 12:00-1:00 PM Pacific at ANB 213, Caltech.
Mar 4, 2026
Talk Announcement: JHU AMS Postdoc Seminar - Learnable Operators on Probability Measures for Ensemble Data Assimilation
I will give a JHU AMS postdoc seminar on Wednesday, March 11, 2026, 12:30-1:30 PM Eastern (9:30-10:30 AM Pacific).
Mar 4, 2026
Learning Enhanced Ensemble Filters
This work introduces the measure neural mapping enhanced ensemble filter (MNMEF), a learning-based data-assimilation method derived from a mean-field formulation of the filtering problem. Measure neural mappings extend neural operators to maps acting on probability measures; their finite-ensemble implementation uses a permutation-invariant set transformer.
Feb 15, 2026
ACM 154: Inverse Problems and Data Assimilation
In winter 2026, I co-taught Caltech ACM 154, Inverse Problems and Data Assimilation, with Prof. Andrew Stuart.
Jan 5, 2026
AGU25 Oral — Learning Enhanced Ensemble Filters
AGU25 oral talk — Tue, Dec 16, 2025, 09:42–09:52 CT (07:42–07:52 PT), Session NG21A.
Nov 2, 2025
Talk Announcement: 1W-MINDS Seminar — Learning Enhanced Ensemble Filters
I will give a 1W-MINDS seminar on Thursday, November 6, 2025 at 2:30 PM Eastern (11:30 AM Pacific).
Nov 1, 2025