Pith. sign in

REVIEW 1 cited by

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2406.14246 v1 pith:IOGO5AMD submitted 2024-06-20 q-bio.QM cs.LGmath.DSstat.ML

Non-Negative Universal Differential Equations With Applications in Systems Biology

classification q-bio.QM cs.LGmath.DSstat.ML
keywords non-negativedifferentialequationsmodelsudesuniversalvaluesadvantages
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Universal differential equations (UDEs) leverage the respective advantages of mechanistic models and artificial neural networks and combine them into one dynamic model. However, these hybrid models can suffer from unrealistic solutions, such as negative values for biochemical quantities. We present non-negative UDE (nUDEs), a constrained UDE variant that guarantees non-negative values. Furthermore, we explore regularisation techniques to improve generalisation and interpretability of UDEs.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Experimental Design for Missing Physics

    stat.ML 2026-03 unverdicted novelty 4.0

    A sequential experimental design technique discriminates between model structures from symbolic regression to discover missing physics in process systems such as bioreactors.