:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Gross, Markus
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2605.31438
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Physics-informed nonlinear vector autoregressive models for the prediction of dynamical systems
by: Adler, James H., et al.
Published: (2024)

A domain decomposition-based autoregressive deep learning model for unsteady and nonlinear partial differential equations
by: Nidhan, Sheel, et al.
Published: (2024)

On autoregressive deep learning models for day-ahead wind power forecasting with irregular shutdowns due to redispatching
by: Meisenbacher, Stefan, et al.
Published: (2024)

Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
by: Kobayashi, Seijin, et al.
Published: (2025)

Probabilistic function-on-function nonlinear autoregressive model for emulation and reliability analysis of dynamical systems
by: Song, Zhouzhou, et al.
Published: (2026)

Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning
by: Benechehab, Abdelhakim, et al.
Published: (2024)

Ancestor regression in structural vector autoregressive models
by: Schultheiss, Christoph, et al.
Published: (2024)

A system identification approach to clustering vector autoregressive time series
by: Yue, Zuogong, et al.
Published: (2025)

Quantum feature-map learning with reduced resource overhead
by: Jäger, Jonas, et al.
Published: (2025)

Uni-Flow: a unified autoregressive-diffusion model for complex multiscale flows
by: Xue, Xiao, et al.
Published: (2026)

On dimensionality of feature vectors in MPNNs
by: Bravo, César, et al.
Published: (2024)

torchtune: PyTorch native post-training library
by: Obozov, Mark, et al.
Published: (2026)

Test time training enhances in-context learning of nonlinear functions
by: Kuwataka, Kento, et al.
Published: (2025)

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

Machine learning for structural design models of continuous beam systems via influence zones
by: Gallet, Adrien, et al.
Published: (2024)

Efficient All-Pairs Correlation Volume Sampling for Optical Flow Estimation
by: Briedis, Karlis Martins, et al.
Published: (2025)

Dragonfly: a modular deep reinforcement learning library
by: Viquerat, Jonathan, et al.
Published: (2025)

Sparse identification of nonlinear dynamics in the presence of library and system uncertainty
by: O'Brien, Andrew
Published: (2024)

Generalizable autoregressive modeling of time series through functional narratives
by: Liu, Ran, et al.
Published: (2024)

Hybrid machine learning models based on physical patterns to accelerate CFD simulations: a short guide on autoregressive models
by: Sengupta, Arindam, et al.
Published: (2025)

JAX-Privacy: A library for differentially private machine learning
by: McKenna, Ryan, et al.
Published: (2026)

Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning
by: Zhu, Libin, et al.
Published: (2023)

A self-supervised learning approach for denoising autoregressive models with additive noise: finite and infinite variance cases
by: Banerjee, Sayantan, et al.
Published: (2025)

A simple mean field model of feature learning
by: Göring, Niclas, et al.
Published: (2025)

Task structure and nonlinearity jointly determine learned representational geometry
by: Alleman, Matteo, et al.
Published: (2024)

Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes
by: Agazzi, Andrea, et al.
Published: (2019)

Deep autoregressive modeling for land use land cover
by: Krapu, Christopher, et al.
Published: (2024)

An empirical study of task and feature correlations in the reuse of pre-trained models
by: Mohamud, Jama Hussein, et al.
Published: (2025)

Reuse out-of-year data to enhance land cover mapping via feature disentanglement and contrastive learning
by: Dantas, Cassio F., et al.
Published: (2024)

Are foundation models useful feature extractors for electroencephalography analysis?
by: Turgut, Özgün, et al.
Published: (2025)

Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime
by: Barboni, Raphaël, et al.
Published: (2025)

Kernel-based optimization of measurement operators for quantum reservoir computers
by: Gross, Markus, et al.
Published: (2026)

Theory and interpretability of Quantum Extreme Learning Machines: a Pauli-transfer matrix approach
by: Gross, Markus, et al.
Published: (2026)

Discrete Stochastic Localization for Non-autoregressive Generation
by: Wu, Yunshu, et al.
Published: (2026)

Completion of partial structures using Patterson maps with the CrysFormer machine learning model
by: Pan, Tom, et al.
Published: (2025)

Non-autoregressive Personalized Bundle Generation
by: Yang, Wenchuan, et al.
Published: (2024)

PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs
by: Brivio, Simone, et al.
Published: (2024)

Online Bayesian system identification in multivariate autoregressive models via message passing
by: Nisslbeck, T. N., et al.
Published: (2025)

Revisiting inverse Hessian vector products for calculating influence functions
by: Klochkov, Yegor, et al.
Published: (2024)

Sparse identification of nonlinear dynamics with library optimization mechanism: Recursive long-term prediction perspective
by: Yonezawa, Ansei, et al.
Published: (2025)