Saved in:
| Main Authors: | Seif, Alireza, Loos, Sarah A. M., Tucci, Gennaro, Roldán, Édgar, Goldt, Sebastian |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2205.14683 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sliding down the stairs: how correlated latent variables accelerate learning with neural networks
by: Bardone, Lorenzo, et al.
Published: (2024)
by: Bardone, Lorenzo, et al.
Published: (2024)
Factual recall in linear associative memories: sharp asymptotics and mechanistic insights
by: Giorlandino, Alessio, et al.
Published: (2026)
by: Giorlandino, Alessio, et al.
Published: (2026)
Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks
by: Székely, Eszter, et al.
Published: (2023)
by: Székely, Eszter, et al.
Published: (2023)
Two failure modes of deep transformers and how to avoid them: a unified theory of signal propagation at initialisation
by: Giorlandino, Alessio, et al.
Published: (2025)
by: Giorlandino, Alessio, et al.
Published: (2025)
Memorisation, convergence and generalisation in generative models
by: Maillard, Antoine, et al.
Published: (2026)
by: Maillard, Antoine, et al.
Published: (2026)
A Fourier perspective on the learning dynamics of neural networks: from sample complexities to mechanistic insights
by: Ricci, Fabiola, et al.
Published: (2026)
by: Ricci, Fabiola, et al.
Published: (2026)
Feature learning from non-Gaussian inputs: the case of Independent Component Analysis in high dimensions
by: Ricci, Fabiola, et al.
Published: (2025)
by: Ricci, Fabiola, et al.
Published: (2025)
Mapping of attention mechanisms to a generalized Potts model
by: Rende, Riccardo, et al.
Published: (2023)
by: Rende, Riccardo, et al.
Published: (2023)
Machine learning for cerebral blood vessels' malformations
by: Topal, Irem, et al.
Published: (2024)
by: Topal, Irem, et al.
Published: (2024)
Stochastic thermodynamics of a probe in a fluctuating correlated field
by: Venturelli, Davide, et al.
Published: (2023)
by: Venturelli, Davide, et al.
Published: (2023)
Boltzmann machine learning and regularization methods for inferring evolutionary fields and couplings from a multiple sequence alignment
by: Miyazawa, Sanzo
Published: (2019)
by: Miyazawa, Sanzo
Published: (2019)
Expanding functional protein sequence space using high entropy generative models
by: Netti, Roberto, et al.
Published: (2026)
by: Netti, Roberto, et al.
Published: (2026)
Quo vadis, stochastic thermodynamics?
by: Korbel, Jan, et al.
Published: (2026)
by: Korbel, Jan, et al.
Published: (2026)
Coding schemes in neural networks learning classification tasks
by: van Meegen, Alexander, et al.
Published: (2024)
by: van Meegen, Alexander, et al.
Published: (2024)
When can in-context learning generalize out of task distribution?
by: Goddard, Chase, et al.
Published: (2025)
by: Goddard, Chase, et al.
Published: (2025)
Demonstration of Robust and Efficient Quantum Property Learning with Shallow Shadows
by: Hu, Hong-Ye, et al.
Published: (2024)
by: Hu, Hong-Ye, et al.
Published: (2024)
Nonreciprocal collective dynamics in a mixture of phoretic Janus colloids
by: Tucci, Gennaro, et al.
Published: (2024)
by: Tucci, Gennaro, et al.
Published: (2024)
Identifying percolation phase transitions with unsupervised learning based on largest clusters
by: Xu, Dian, et al.
Published: (2023)
by: Xu, Dian, et al.
Published: (2023)
Model-free learning of probability flows: Elucidating the nonequilibrium dynamics of flocking
by: Boffi, Nicholas M., et al.
Published: (2024)
by: Boffi, Nicholas M., et al.
Published: (2024)
A simple reconstruction method to infer nonreciprocal interactions and local driving in complex systems
by: Hempel, Tim, et al.
Published: (2024)
by: Hempel, Tim, et al.
Published: (2024)
Fundamentals of quantum Boltzmann machine learning with visible and hidden units
by: Wilde, Mark M.
Published: (2025)
by: Wilde, Mark M.
Published: (2025)
How does Chain of Thought decompose complex tasks?
by: Nadgir, Amrut, et al.
Published: (2026)
by: Nadgir, Amrut, et al.
Published: (2026)
Finite-time transitions in optimal control and non-equilibrium relaxation
by: Meibohm, Jan, et al.
Published: (2026)
by: Meibohm, Jan, et al.
Published: (2026)
Interpretable machine learning of amino acid patterns in proteins: a statistical ensemble approach
by: Braghetto, Anna, et al.
Published: (2023)
by: Braghetto, Anna, et al.
Published: (2023)
Hydrodynamic stresses in a multi-species suspension of active Janus colloids
by: Tucci, Gennaro, et al.
Published: (2025)
by: Tucci, Gennaro, et al.
Published: (2025)
On the area swept by a biased diffusion till its first-exit time: Martingale approach and gambling opportunities
by: Sarmiento, Yonathan, et al.
Published: (2023)
by: Sarmiento, Yonathan, et al.
Published: (2023)
Maximum diffusion reinforcement learning
by: Berrueta, Thomas A., et al.
Published: (2023)
by: Berrueta, Thomas A., et al.
Published: (2023)
Geometric origin of adversarial vulnerability in deep learning
by: Ren, Yixiong, et al.
Published: (2025)
by: Ren, Yixiong, et al.
Published: (2025)
Machine learning for structure-property relationships: Scalability and limitations
by: Tian, Zhongzheng, et al.
Published: (2023)
by: Tian, Zhongzheng, et al.
Published: (2023)
Quantum-data-driven dynamical transition in quantum learning
by: Zhang, Bingzhi, et al.
Published: (2024)
by: Zhang, Bingzhi, et al.
Published: (2024)
Controlling dynamics of stochastic systems with deep reinforcement learning
by: Mukhamadiarov, Ruslan
Published: (2025)
by: Mukhamadiarov, Ruslan
Published: (2025)
Pareto fronts and trade-off relations from exact multi-objective optimization of thermal machines
by: Almanza-Marrero, José A., et al.
Published: (2026)
by: Almanza-Marrero, José A., et al.
Published: (2026)
Interpretable representation learning of quantum data enabled by probabilistic variational autoencoders
by: de Schoulepnikoff, Paulin, et al.
Published: (2025)
by: de Schoulepnikoff, Paulin, et al.
Published: (2025)
Exactly solvable diffusions from space-time transformations
by: Di Bello, Costantino, et al.
Published: (2025)
by: Di Bello, Costantino, et al.
Published: (2025)
Pseudo-likelihood produces associative memories able to generalize, even for asymmetric couplings
by: D'Amico, Francesco, et al.
Published: (2025)
by: D'Amico, Francesco, et al.
Published: (2025)
Generalization Dynamics of Linear Diffusion Models
by: Merger, Claudia, et al.
Published: (2025)
by: Merger, Claudia, et al.
Published: (2025)
Active particles in moving traps: minimum work protocols and information efficiency of work extraction
by: Schüttler, Janik, et al.
Published: (2025)
by: Schüttler, Janik, et al.
Published: (2025)
Optimal closed-loop control of active particles and a minimal information engine
by: Garcia-Millan, Rosalba, et al.
Published: (2024)
by: Garcia-Millan, Rosalba, et al.
Published: (2024)
Meta-learning of Gibbs states for many-body Hamiltonians with applications to Quantum Boltzmann Machines
by: Bhat, Ruchira V, et al.
Published: (2025)
by: Bhat, Ruchira V, et al.
Published: (2025)
Unsupervised learning of anomalous diffusion data
by: Muñoz-Gil, Gorka, et al.
Published: (2021)
by: Muñoz-Gil, Gorka, et al.
Published: (2021)
Similar Items
-
Sliding down the stairs: how correlated latent variables accelerate learning with neural networks
by: Bardone, Lorenzo, et al.
Published: (2024) -
Factual recall in linear associative memories: sharp asymptotics and mechanistic insights
by: Giorlandino, Alessio, et al.
Published: (2026) -
Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks
by: Székely, Eszter, et al.
Published: (2023) -
Two failure modes of deep transformers and how to avoid them: a unified theory of signal propagation at initialisation
by: Giorlandino, Alessio, et al.
Published: (2025) -
Memorisation, convergence and generalisation in generative models
by: Maillard, Antoine, et al.
Published: (2026)