:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Janik, Konrad, Benner, Peter
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2509.20212
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Time-adaptive SympNets for separable Hamiltonian systems
by: Janik, Konrad, et al.
Published: (2025)

Symplectic convolutional neural networks
by: Yıldız, Süleyman, et al.
Published: (2025)

Data-Driven Identification of Quadratic Representations for Nonlinear Hamiltonian Systems using Weakly Symplectic Liftings
by: Yildiz, Süleyman, et al.
Published: (2023)

Interpretable Spatial-Temporal Fusion Transformers: Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs
by: Sun, Shuwen, et al.
Published: (2025)

Generalized Quadratic Embeddings for Nonlinear Dynamics using Deep Learning
by: Goyal, Pawan, et al.
Published: (2022)

Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning
by: Goyal, Pawan, et al.
Published: (2021)

Data-Augmented Predictive Deep Neural Network: Enhancing the extrapolation capabilities of non-intrusive surrogate models
by: Sun, Shuwen, et al.
Published: (2024)

Structure-preserving learning for multi-symplectic PDEs
by: Yıldız, Süleyman, et al.
Published: (2024)

Comparative Analysis of Predicting Subsequent Steps in Hénon Map
by: S, Vismaya V, et al.
Published: (2024)

Stability-Certified Learning of Control Systems with Quadratic Nonlinearities
by: Duff, Igor Pontes, et al.
Published: (2024)

Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference
by: Goyal, Pawan, et al.
Published: (2023)

SynCoTrain: A Dual Classifier PU-learning Framework for Synthesizability Prediction
by: Amariamir, Sasan, et al.
Published: (2024)

GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations
by: Forootani, Ali, et al.
Published: (2024)

GFlowNets for Hamiltonian decomposition in groups of compatible operators
by: Huidobro-Meezs, Isaac L., et al.
Published: (2024)

Subspace-Distance-Enabled Active Learning for Efficient Data-Driven Model Reduction of Parametric Dynamical Systems
by: Kapadia, Harshit, et al.
Published: (2025)

Deep Neural Nets as Hamiltonians
by: Winer, Mike, et al.
Published: (2025)

Aspects of human memory and Large Language Models
by: Janik, Romuald A.
Published: (2023)

Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
by: Zhong, Yaofeng Desmond, et al.
Published: (2019)

GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo
by: Bou-Rabee, Nawaf, et al.
Published: (2024)

Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets
by: Jacot, Arthur, et al.
Published: (2024)

Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
by: Zaspel, Peter, et al.
Published: (2024)

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models
by: Hagemann, Paul, et al.
Published: (2025)

A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas
by: Benzin, Janik-Vasily, et al.
Published: (2023)

Learning reduced-order Quadratic-Linear models in Process Engineering using Operator Inference
by: Gosea, Ion Victor, et al.
Published: (2024)

Hamiltonian Score Matching and Generative Flows
by: Holderrieth, Peter, et al.
Published: (2024)

Hamiltonian Neural Networks for Robust Out-of-Time Credit Scoring
by: Marín, Javier
Published: (2024)

DCSI -- An improved measure of cluster separability based on separation and connectedness
by: Gauss, Jana, et al.
Published: (2023)

When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
by: Treven, Lenart, et al.
Published: (2024)

Solve sparse PCA problem by employing Hamiltonian system and leapfrog method
by: Tran, Loc Hoang
Published: (2025)

Learning partially observed systems with neural Hamiltonian ordinary differential equations
by: Meltzer, Sunniva, et al.
Published: (2026)

Evaluating the printability of stl files with ML
by: Henn, Janik, et al.
Published: (2025)

Selective Encryption using Segmentation Mask with Chaotic Henon Map for Multidimensional Medical Images
by: Prakash, S Arut, et al.
Published: (2024)

Predicting adaptively chosen observables in quantum systems
by: Huang, Jerry, et al.
Published: (2024)

Unsupervised domain adaptation for radioisotope identification in gamma spectroscopy
by: Lalor, Peter, et al.
Published: (2026)

Hamiltonian-based neural networks for systems under nonholonomic constraints
by: T., Ignacio Puiggros, et al.
Published: (2024)

Hamiltonian Graph Inference Networks: Joint structure discovery and dynamics prediction for lattice Hamiltonian systems from trajectory data
by: Geng, Ru, et al.
Published: (2026)

BiTimeCrossNet: Time-Aware Self-Supervised Learning for Pediatric Sleep
by: Pandey, Saurav Raj, et al.
Published: (2026)

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting
by: Xing, Xiaoyan, et al.
Published: (2024)

In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks
by: Xu, Shangqing, et al.
Published: (2026)

Scalable h-adaptive probabilistic solver for time-independent and time-dependent systems
by: Thakur, Akshay, et al.
Published: (2025)