Cover Image

Spectral Normalization and Voigt-Reuss net: A universal approach to microstructure-property forecasting with physical guarantees

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Keshav, Sanath, Herb, Julius, Fritzen, Felix
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Spectral Normalization and Voigt–Reuss net: A universal approach to microstructure‐property forecasting with physical guarantees
by: Sanath Keshav, et al.
Published: (2025)

Robust inverse material design with physical guarantees using the Voigt-Reuss Net
by: Keshav, Sanath, et al.
Published: (2025)

Robust Inverse Material Design With Physical Guarantees Using the Voigt‐Reuss Net
by: Sanath Keshav, et al.
Published: (2026)

Accelerating Conjugate Gradient Solvers for Homogenization Problems with Unitary Neural Operators
by: Herb, Julius, et al.
Published: (2025)

Accelerating Conjugate Gradient Solvers for Homogenization Problems With Unitary Neural Operators
by: Julius Herb, et al.
Published: (2026)

A universal policy wrapper with guarantees
by: Bolychev, Anton, et al.
Published: (2025)

Generalization is not a universal guarantee: Estimating similarity to training data with an ensemble out-of-distribution metric
by: Schreyer, W. Max, et al.
Published: (2025)

A theoretical framework for M-posteriors: frequentist guarantees and robustness properties
by: Marusic, Juraj, et al.
Published: (2025)

Detecting Token-Level Hallucinations Using Variance Signals: A Reference-Free Approach
by: Kumar, Keshav
Published: (2025)

PRISM: A hierarchical multiscale approach for time series forecasting
by: Chen, Zihao, et al.
Published: (2025)

Neural Normalized Cut: A Differential and Generalizable Approach for Spectral Clustering
by: He, Wei, et al.
Published: (2025)

Adaptive tumor growth forecasting via neural & universal ODEs
by: Subramanian, Kavya, et al.
Published: (2025)

A theoretical guarantee for SyncRank
by: Rao, Yang
Published: (2025)

Theoretical guarantees for neural estimators in parametric statistics
by: Rödder, Almut, et al.
Published: (2025)

Revisiting inference after prediction
by: Motwani, Keshav, et al.
Published: (2023)

Data-driven identification of latent port-Hamiltonian systems
by: Rettberg, Johannes, et al.
Published: (2024)

Multivariate Scenario Generation of Day-Ahead Electricity Prices using Normalizing Flows
by: Hilger, Hannes, et al.
Published: (2023)

Informed Spectral Normalized Gaussian Processes for Trajectory Prediction
by: Schlauch, Christian, et al.
Published: (2024)

Revisiting RIP guarantees for sketching operators on mixture models
by: Belhadji, Ayoub, et al.
Published: (2023)

Data-driven robust Markov decision processes on Borel spaces: performance guarantees via an axiomatic approach
by: Ramani, Sivaramakrishnan
Published: (2026)

Deep Ritz method with Fourier feature mapping: A deep learning approach for solving variational models of microstructure
by: Mema, Ensela, et al.
Published: (2025)

Federated learning over physical channels: adaptive algorithms with near-optimal guarantees
by: Zhang, Rui, et al.
Published: (2025)

Theoretical guarantees in KL for Diffusion Flow Matching
by: Silveri, Marta Gentiloni, et al.
Published: (2024)

Kernel-based guarantees for nonlinear parametric models in Bayesian optimization
by: Oliveira, Rafael
Published: (2026)

DPOT: A DeepParticle method for Computation of Optimal Transport with convergence guarantee
by: Li, Yingyuan, et al.
Published: (2025)

On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
by: Draxler, Felix, et al.
Published: (2024)

Statistical guarantees for denoising reflected diffusion models
by: Holk, Asbjørn, et al.
Published: (2024)

Proximal basin hopping: global optimization with guarantees
by: Lauga, Guillaume, et al.
Published: (2026)

Evolutionary scheduling of university activities based on consumption forecasts to minimise electricity costs
by: Ruddick, Julian, et al.
Published: (2022)

Optimizing accuracy and diversity: a multi-task approach to forecast combinations
by: Felici, Giovanni, et al.
Published: (2023)

Spectral Normalization for Lipschitz-Constrained Policies on Learning Humanoid Locomotion
by: Shin, Jaeyong, et al.
Published: (2025)

Robust Post-Training for Generative Recommenders: Why Exponential Reward-Weighted SFT Outperforms RLHF
by: Chidambaram, Keertana, et al.
Published: (2026)

Differential privacy guarantees of Markov chain Monte Carlo algorithms
by: Bertazzi, Andrea, et al.
Published: (2025)

Online scalable Gaussian processes with conformal prediction for guaranteed coverage
by: Xu, Jinwen, et al.
Published: (2024)

A two-step machine learning approach to statistical post-processing of weather forecasts for power generation
by: Baran, Ágnes, et al.
Published: (2022)

Kernel-based learning with guarantees for multi-agent applications
by: Kowalczyk, Krzysztof, et al.
Published: (2024)

Universal generalization guarantees for Wasserstein distributionally robust models
by: Le, Tam, et al.
Published: (2024)

A unifying account of warm start guarantees for patches of quantum landscapes
by: Mhiri, Hela, et al.
Published: (2025)

Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting
by: Rice, Julian, et al.
Published: (2020)

A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
by: Li, Shuyao, et al.
Published: (2023)