Research

General Explicit Network (GEN): A novel deep learning architecture for solving partial differential equations

Novel deep learning architecture GEN directly solves partial differential equations, merging neural networks with physics-informed computational mathematics.

Tuesday, April 7, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline

General Explicit Network (GEN) is a novel deep learning architecture designed to solve partial differential equations. The research contributes to physics-informed machine learning by proposing a new neural network approach for PDEs. This work bridges deep learning and computational mathematics.

Read original at arXiv CS.LG (Machine Learning)

Curiosity-Critic: Cumulative Prediction Error Improvement as a Tractable Intrinsic Reward for World Model Training

New intrinsic reward mechanism using cumulative prediction error replaces expensive curiosity signals to improve world model training efficiency.

PolicyApr 22

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