Saved in:
| Main Author: | Maurer, Andreas |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.14469 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Generalization of the Gibbs algorithm with high probability at low temperatures
by: Maurer, Andreas
Published: (2025)
by: Maurer, Andreas
Published: (2025)
An Empirical Bernstein Inequality for Dependent Data in Hilbert Spaces and Applications
by: Mirzaei, Erfan, et al.
Published: (2025)
by: Mirzaei, Erfan, et al.
Published: (2025)
Hamiltonian Score Matching and Generative Flows
by: Holderrieth, Peter, et al.
Published: (2024)
by: Holderrieth, Peter, et al.
Published: (2024)
Improved algorithms for learning quantum Hamiltonians, via flat polynomials
by: Narayanan, Shyam
Published: (2024)
by: Narayanan, Shyam
Published: (2024)
Parametric modeling of shear wave velocity profiles for the conterminous U.S
by: Sanger, Morgan D., et al.
Published: (2025)
by: Sanger, Morgan D., et al.
Published: (2025)
Simple algorithms to test and learn local Hamiltonians
by: Gutiérrez, Francisco Escudero
Published: (2024)
by: Gutiérrez, Francisco Escudero
Published: (2024)
Generalization error of spectral algorithms
by: Velikanov, Maksim, et al.
Published: (2024)
by: Velikanov, Maksim, et al.
Published: (2024)
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
by: Chen, Yuansi, et al.
Published: (2023)
by: Chen, Yuansi, et al.
Published: (2023)
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
by: McLennan, Luke, et al.
Published: (2025)
by: McLennan, Luke, et al.
Published: (2025)
Learning Generalized Hamiltonians using fully Symplectic Mappings
by: Choudhary, Harsh, et al.
Published: (2024)
by: Choudhary, Harsh, et al.
Published: (2024)
Hamiltonian-based Quantum Reinforcement Learning for Neural Combinatorial Optimization
by: Kruse, Georg, et al.
Published: (2024)
by: Kruse, Georg, et al.
Published: (2024)
Hamiltonian Property Testing
by: Bluhm, Andreas, et al.
Published: (2024)
by: Bluhm, Andreas, et al.
Published: (2024)
From superposition to sparse codes: interpretable representations in neural networks
by: Klindt, David, et al.
Published: (2025)
by: Klindt, David, et al.
Published: (2025)
Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks
by: Maurer, Nathan, et al.
Published: (2025)
by: Maurer, Nathan, et al.
Published: (2025)
Stable Port-Hamiltonian Neural Networks
by: Roth, Fabian J., et al.
Published: (2025)
by: Roth, Fabian J., et al.
Published: (2025)
Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm
by: Renard, Titouan, et al.
Published: (2024)
by: Renard, Titouan, et al.
Published: (2024)
Counterdiabatic Hamiltonian Monte Carlo
by: Cohn-Gordon, Reuben, et al.
Published: (2026)
by: Cohn-Gordon, Reuben, et al.
Published: (2026)
Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densities
by: Tran, Jimmy Huy, et al.
Published: (2025)
by: Tran, Jimmy Huy, et al.
Published: (2025)
Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network
by: Chen, Chen, et al.
Published: (2025)
by: Chen, Chen, et al.
Published: (2025)
UniFField: A Generalizable Unified Neural Feature Field for Visual, Semantic, and Spatial Uncertainties in Any Scene
by: Maurer, Christian, et al.
Published: (2025)
by: Maurer, Christian, et al.
Published: (2025)
Memory-Efficient Optimization with Factorized Hamiltonian Descent
by: Nguyen, Son, et al.
Published: (2024)
by: Nguyen, Son, et al.
Published: (2024)
Generalizing soft actor-critic algorithms to discrete action spaces
by: Zhang, Le, et al.
Published: (2024)
by: Zhang, Le, et al.
Published: (2024)
Learning Hamiltonian Density Using DeepONet
by: Xu, Baige, et al.
Published: (2025)
by: Xu, Baige, et al.
Published: (2025)
ODE approximation for the Adam algorithm: General and overparametrized setting
by: Dereich, Steffen, et al.
Published: (2025)
by: Dereich, Steffen, et al.
Published: (2025)
Separable Hamiltonian Neural Networks
by: Khoo, Zi-Yu, et al.
Published: (2023)
by: Khoo, Zi-Yu, et al.
Published: (2023)
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning
by: Song, Yeongwoo, et al.
Published: (2022)
by: Song, Yeongwoo, et al.
Published: (2022)
Automated Immunophenotyping Assessment for Diagnosing Childhood Acute Leukemia using Set-Transformers
by: Lygizou, Elpiniki Maria, et al.
Published: (2024)
by: Lygizou, Elpiniki Maria, et al.
Published: (2024)
Time-adaptive HénonNets for separable Hamiltonian systems
by: Janik, Konrad, et al.
Published: (2025)
by: Janik, Konrad, et al.
Published: (2025)
Time-adaptive SympNets for separable Hamiltonian systems
by: Janik, Konrad, et al.
Published: (2025)
by: Janik, Konrad, et al.
Published: (2025)
Hamiltonian Neural PDE Solvers through Functional Approximation
by: Zhou, Anthony, et al.
Published: (2025)
by: Zhou, Anthony, et al.
Published: (2025)
Detecting outliers by clustering algorithms
by: Li, Qi, et al.
Published: (2024)
by: Li, Qi, et al.
Published: (2024)
Is your algorithm unlearning or untraining?
by: Triantafillou, Eleni, et al.
Published: (2026)
by: Triantafillou, Eleni, et al.
Published: (2026)
Denoising Hamiltonian Network for Physical Reasoning
by: Deng, Congyue, et al.
Published: (2025)
by: Deng, Congyue, et al.
Published: (2025)
Practical Black Box Hamiltonian Learning
by: Gu, Andi, et al.
Published: (2022)
by: Gu, Andi, et al.
Published: (2022)
Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient
by: Dinh, Vu C., et al.
Published: (2024)
by: Dinh, Vu C., et al.
Published: (2024)
Hamiltonian Neural Networks for Robust Out-of-Time Credit Scoring
by: Marín, Javier
Published: (2024)
by: Marín, Javier
Published: (2024)
Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach
by: Friedl, Katharina, et al.
Published: (2025)
by: Friedl, Katharina, et al.
Published: (2025)
Port-Hamiltonian Neural Networks with Output Error Noise Models
by: Moradi, Sarvin, et al.
Published: (2025)
by: Moradi, Sarvin, et al.
Published: (2025)
H-FEX: A Symbolic Learning Method for Hamiltonian Systems
by: Lai, Jasen, et al.
Published: (2025)
by: Lai, Jasen, et al.
Published: (2025)
Machine Learning Hamiltonian Dynamical Systems with Sparse and Noisy Data
by: Thapar, Vedanta, et al.
Published: (2026)
by: Thapar, Vedanta, et al.
Published: (2026)
Similar Items
-
Generalization of the Gibbs algorithm with high probability at low temperatures
by: Maurer, Andreas
Published: (2025) -
An Empirical Bernstein Inequality for Dependent Data in Hilbert Spaces and Applications
by: Mirzaei, Erfan, et al.
Published: (2025) -
Hamiltonian Score Matching and Generative Flows
by: Holderrieth, Peter, et al.
Published: (2024) -
Improved algorithms for learning quantum Hamiltonians, via flat polynomials
by: Narayanan, Shyam
Published: (2024) -
Parametric modeling of shear wave velocity profiles for the conterminous U.S
by: Sanger, Morgan D., et al.
Published: (2025)