RLNS regularizes LNS to perform block Gibbs sampling under entropy, interpolating between pseudolikelihood and exact MLE for differentiable combinatorial optimization.
The elements of differentiable program- ming
9 Pith papers cite this work. Polarity classification is still indexing.
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A framework learns constitutive priors from noisy data to enable PDE-constrained inverse design of elastic networks using latent variables, homotopy continuation, Chamfer distance matching, and neural smoothness constraints.
Jeffreys prior over EFTofLSS coefficients mitigates projection effects in DESI DR1 power spectrum multipole fits, recentering posteriors for late-time expansion parameters.
AD-MPCC integrates differentiable MPCC, online Pacejka parameter estimation via moving-horizon methods, and a supervised ML model to adapt objective weights, yielding safer and faster simulated laps on varying surfaces.
DIFFRACT develops a duality theory for standard interference functions to unroll iterative algorithms into differentiable neural architectures for end-to-end learning in wireless resource management.
A feedback optimization pipeline for tri-level mobility games outperforms Bayesian optimization and genetic algorithms on Zurich multimodal data while identifying incentives that boost multimodal use.
Differentiable physics recovers accurate wall shear stress from concentration observations across measurement scenarios where PINNs fail.
This perspective paper categorizes hybrid architectures for combining mechanistic and data-driven models using residual learning, Neural ODEs, and solver-in-the-loop to model neurological disorder progression.
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Wall Shear Stress Reconstruction from Concentration: Differentiable Physics and Physics-Informed Neural Networks
Differentiable physics recovers accurate wall shear stress from concentration observations across measurement scenarios where PINNs fail.