Probabilistic implicit neural representations for irregular multivariate time series, giving individualized imputation and forecasting in a single forward pass, with no per-series fine-tuning.
Aug 15, 2026
A foundation model for macroeconomic forecasting, built on Moirai and fine-tuned on multi-country economic data for probabilistic, zero-shot forecasts of economic indicators.
Dec 1, 2025
Latent diffusion over implicit neural representations, using a Transformer hypernetwork decoder that can be trained from scratch or "hyper-transformed" from a pre-trained LDM.
Jul 1, 2025
A lighter probabilistic transformer for multivariate forecasting, released with the first public re-implementation of the ProTran baseline, including a corrected ELBO.
Nov 26, 2024
Learns distributions over functions by combining hypernetworks with a mixture of generators, so the same model handles images, 3D shapes and climate data, including point-dropout settings.
Aug 1, 2023
A compact notebook that builds a neural ODE from first principles with an explicit Euler solver. It was a stepping stone to my work on deep generative second-order ODEs (ODE2VAE).
Aug 26, 2020