3 papers
cs.LG2026
Scaling Effects and Uncertainty Quantification in Neural Actor Critic Algorithms
Nikos Georgoudios, Konstantinos Spiliopoulos, Justin Sirignano
We investigate the neural Actor Critic algorithm using shallow neural networks for both the Actor and Critic models. The focus of this work is twofold: first, to compare the conver…
cs.LG2025
Global Convergence of Adjoint-Optimized Neural PDEs
Konstantin Riedl, Justin Sirignano, Konstantinos Spiliopoulos
Many engineering and scientific fields have recently become interested in modeling terms in partial differential equations (PDEs) with neural networks, which requires solving the i…
cs.LG2025
Convergence Analysis of Real-time Recurrent Learning (RTRL) for a class of Recurrent Neural Networks
Samuel Chun-Hei Lam, Justin Sirignano, Konstantinos Spiliopoulos
Recurrent neural networks (RNNs) are commonly trained with the truncated backpropagation-through-time (TBPTT) algorithm. For the purposes of computational tractability, the TBPTT a…