Jan Drgona — accepted AI-conference papers

2026

Cardinality-Invariant Neural Operator Policies for Scalable PDE Control

Pietro Zanotta, Dibakar Sarkar, Honghui Zheng, Somdatta Goswami, Jan Drgona

ICML 2026poster

Controlling partial differential equations (PDEs) with learning-based policies remains fundamentally limited by fixed-dimensional representations: policies trained for a specific sensor, actuator, or agent configuration typically fail when the configuration changes. This limitation is particularly s…

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2021

On the Stochastic Stability of Deep Markov Models

Jan Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Y Liu, Mahantesh Halappanavar

NeurIPS 2021poster

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we pres…

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