AI Paper Atlas

Research map / Probabilistic and scientific modeling / Differential equations and PDEs

Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting

ICLR 2021 · Probabilistic and scientific modeling › Differential equations and PDEs · approach: Physics-informed operator learning · 113 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
augment incomplete physical dynamics with a learned residual constrained to have minimal normAPHYNITY · Reaction-diffusionlog MSE: -1.26±0.02 -> -5.10±0.21Helped
augment incomplete physical dynamics with a learned residual constrained to have minimal normAPHYNITY · Wave equationlog MSE: 0.51±0.07 -> -4.64±0.25Helped
augment incomplete physical dynamics with a learned residual constrained to have minimal normAPHYNITY · Damped pendulumlog MSE: -0.14±0.10 -> -7.86±0.60Helped
replace APHYNITY decomposition with vanilla augmentation (ablation)Param PDE (a,b) on reaction-diffusion · Reaction-diffusionlog MSE: -5.10±0.21 -> -4.56±0.52Hurt
replace APHYNITY decomposition with vanilla augmentation (ablation)Param PDE (a,b,k) on reaction-diffusion · Reaction-diffusionlog MSE: -9.35±0.02 -> -8.04±0.03Hurt
replace APHYNITY decomposition with vanilla augmentation (ablation)Param PDE (c) on wave equation · Wave equationlog MSE: -4.64±0.25 -> -3.90 ± 0.27Hurt
replace APHYNITY decomposition with vanilla augmentation (ablation)Param PDE (c,k) on wave equation · Wave equationlog MSE: -6.09±0.28 -> -5.96 ± 0.10Hurt
replace APHYNITY decomposition with vanilla augmentation (ablation)Hamiltonian pendulum model · Damped pendulumlog MSE: -3.97±1.2 -> -0.35±0.1Hurt
replace APHYNITY decomposition with vanilla augmentation (ablation)Param ODE (ω0,α) on damped pendulum · Damped pendulumlog MSE: -8.31±0.3 -> -7.60±0.6Hurt
use trajectory-based supervision instead of finite-difference derivative supervision (ablation)APHYNITY · Reaction-diffusion, wave equation, and damped pendulumforecasting accuracyHelped
use adaptive optimization of the trajectory-loss weight instead of fixing λ=1 and τ2=0 (ablation)APHYNITY · Reaction-diffusion, wave equation, and damped pendulumforecasting accuracyHelped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy