Center for Advanced Intelligence Project

The talk will be held in a hybrid format, both in person at AIP Open Space of RIKEN AIP (Nihombashi office) and online by Zoom. AIP Open Space: only available to AIP researchers.

Date: March 28 2025

Time: 14:00

Speaker: Giacomo Turri (Italian Institute of Technology)

Title: Neural Conditional Probability for Uncertainty Quantification

Abstract:
We introduce Neural Conditional Probability (NCP), an operator-theoretic approach to learning conditional distributions with a focus on statistical inference tasks. NCP can be used to build conditional confidence regions and extract key statistics such as conditional quantiles, mean, and covariance. It offers streamlined learning via a single unconditional training phase, allowing efficient inference without the need for retraining even when conditioning changes. By leveraging the approximation capabilities of neural networks, NCP efficiently handles a wide variety of complex probability distributions. We provide theoretical guarantees that ensure both optimization consistency and statistical accuracy. In experiments, we show that NCP with a 2-hidden-layer network matches or outperforms leading methods. This demonstrates that a minimalistic architecture with a theoretically grounded loss can achieve competitive results, even in the face of more complex architectures.

Host: Minh Ha Quang