Saved in:
| Main Authors: | Doshi, Darshil, He, Tianyu, Das, Aritra, Gromov, Andrey |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.03495 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
by: He, Tianyu, et al.
Published: (2024)
by: He, Tianyu, et al.
Published: (2024)
To grok or not to grok: Disentangling generalization and memorization on corrupted algorithmic datasets
by: Doshi, Darshil, et al.
Published: (2023)
by: Doshi, Darshil, et al.
Published: (2023)
Spectral Flow for the Riemann zeros
by: LeClair, André
Published: (2024)
by: LeClair, André
Published: (2024)
Opening the Black Box: predicting the trainability of deep neural networks with reconstruction entropy
by: Thurn, Yanick, et al.
Published: (2024)
by: Thurn, Yanick, et al.
Published: (2024)
Wilsonian Renormalization of Neural Network Gaussian Processes
by: Howard, Jessica N., et al.
Published: (2024)
by: Howard, Jessica N., et al.
Published: (2024)
Bayesian RG Flow in Neural Network Field Theories
by: Howard, Jessica N., et al.
Published: (2024)
by: Howard, Jessica N., et al.
Published: (2024)
Topological Effects in Neural Network Field Theory
by: Ferko, Christian, et al.
Published: (2026)
by: Ferko, Christian, et al.
Published: (2026)
Lecture Notes on Statistical Physics and Neural Networks
by: Hohm, Olaf
Published: (2026)
by: Hohm, Olaf
Published: (2026)
A Two-Phase Perspective on Deep Learning Dynamics
by: Koch, Robert de Mello, et al.
Published: (2025)
by: Koch, Robert de Mello, et al.
Published: (2025)
Gauge-covariant stochastic neural fields: Stability and finite-width effects
by: Terin, Rodrigo Carmo
Published: (2025)
by: Terin, Rodrigo Carmo
Published: (2025)
Neural Network Quantum Field Theory from Transformer Architectures
by: Ageev, Dmitry S., et al.
Published: (2026)
by: Ageev, Dmitry S., et al.
Published: (2026)
The Underlying Scaling Laws and Universal Statistical Structure of Complex Datasets
by: Levi, Noam, et al.
Published: (2023)
by: Levi, Noam, et al.
Published: (2023)
Neural Scaling Laws From Large-N Field Theory: Solvable Model Beyond the Ridgeless Limit
by: Zhang, Zhengkang
Published: (2024)
by: Zhang, Zhengkang
Published: (2024)
The neural networks with tensor weights and emergent fermionic Wick rules in the large-width limit
by: Huang, Guojun, et al.
Published: (2025)
by: Huang, Guojun, et al.
Published: (2025)
Learning topological defects formation with neural networks in a quantum phase transition
by: Shi, Han-Qing, et al.
Published: (2022)
by: Shi, Han-Qing, et al.
Published: (2022)
(How) Can Transformers Predict Pseudo-Random Numbers?
by: Tao, Tao, et al.
Published: (2025)
by: Tao, Tao, et al.
Published: (2025)
Towards Worst-Case Guarantees with Scale-Aware Interpretability
by: Greenspan, Lauren, et al.
Published: (2026)
by: Greenspan, Lauren, et al.
Published: (2026)
Robust Reasoning as a Symmetry-Protected Topological Phase
by: Sung, Ilmo
Published: (2026)
by: Sung, Ilmo
Published: (2026)
Detecting quantum chaos via pseudo-entropy
by: He, Song, et al.
Published: (2024)
by: He, Song, et al.
Published: (2024)
Random matrix theory of sparse neuronal networks with heterogeneous timescales
by: Chotibut, Thiparat, et al.
Published: (2025)
by: Chotibut, Thiparat, et al.
Published: (2025)
Crumpled-to-flat transition of quenched disordered membranes at two-loop order
by: Delzescaux, L., et al.
Published: (2024)
by: Delzescaux, L., et al.
Published: (2024)
Magnetic exponent for the long-range bond disordered Potts model
by: Lecce, Ivan, et al.
Published: (2024)
by: Lecce, Ivan, et al.
Published: (2024)
The quantum $p$-spin renormalization group in the large $N$ limit as a benchmark for functional renormalization group
by: Lahoche, Vincent, et al.
Published: (2024)
by: Lahoche, Vincent, et al.
Published: (2024)
On the breakdown of dimensional reduction and supersymmetry in random-field models
by: Tarjus, Gilles, et al.
Published: (2024)
by: Tarjus, Gilles, et al.
Published: (2024)
An intriguing connection between Pisarski's fixed point and (2+3)-spin glasses
by: Lahoche, Vincent, et al.
Published: (2024)
by: Lahoche, Vincent, et al.
Published: (2024)
Conformal Invariance and Multifractality at Anderson Transitions in Arbitrary Dimensions
by: Padayasi, Jaychandran, et al.
Published: (2023)
by: Padayasi, Jaychandran, et al.
Published: (2023)
Theory of Anderson localization on the hyperbolic plane
by: Altland, Alexander, et al.
Published: (2026)
by: Altland, Alexander, et al.
Published: (2026)
Functional Renormalization Group Approach for Signal Detection
by: Lahoche, Vincent, et al.
Published: (2022)
by: Lahoche, Vincent, et al.
Published: (2022)
Excited String States and D-branes from Infinite Width Neural Networks
by: Ageev, Dmitry S., et al.
Published: (2026)
by: Ageev, Dmitry S., et al.
Published: (2026)
Roughness and critical force for depinning at 3-loop order
by: Semeikin, Mikhail N., et al.
Published: (2023)
by: Semeikin, Mikhail N., et al.
Published: (2023)
Exact generating function of a zero-dimensional supersymmetric non-linear sigma model
by: Rançon, Adam, et al.
Published: (2020)
by: Rançon, Adam, et al.
Published: (2020)
Neural network representation of quantum systems
by: Hashimoto, Koji, et al.
Published: (2024)
by: Hashimoto, Koji, et al.
Published: (2024)
Towards Distributed Neural Architectures
by: Cowsik, Aditya, et al.
Published: (2025)
by: Cowsik, Aditya, et al.
Published: (2025)
Deep learning lattice gauge theories
by: Apte, Anuj, et al.
Published: (2024)
by: Apte, Anuj, et al.
Published: (2024)
Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees
by: Miyagawa, Taiki, et al.
Published: (2024)
by: Miyagawa, Taiki, et al.
Published: (2024)
Emergent multifractality in power-law decaying eigenstates
by: Das, Adway Kumar, et al.
Published: (2025)
by: Das, Adway Kumar, et al.
Published: (2025)
Spectral Form Factors of Topological Phases
by: Sarkar, Anurag, et al.
Published: (2023)
by: Sarkar, Anurag, et al.
Published: (2023)
Gauge covariant neural network for quarks and gluons
by: Nagai, Yuki, et al.
Published: (2021)
by: Nagai, Yuki, et al.
Published: (2021)
Synaptic Field Theory for Neural Networks
by: Lee, Donghee, et al.
Published: (2025)
by: Lee, Donghee, et al.
Published: (2025)
Learning holographic QCD with unflavoured meson spectra
by: Arun, Mathew Thomas, et al.
Published: (2025)
by: Arun, Mathew Thomas, et al.
Published: (2025)
Similar Items
-
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
by: He, Tianyu, et al.
Published: (2024) -
To grok or not to grok: Disentangling generalization and memorization on corrupted algorithmic datasets
by: Doshi, Darshil, et al.
Published: (2023) -
Spectral Flow for the Riemann zeros
by: LeClair, André
Published: (2024) -
Opening the Black Box: predicting the trainability of deep neural networks with reconstruction entropy
by: Thurn, Yanick, et al.
Published: (2024) -
Wilsonian Renormalization of Neural Network Gaussian Processes
by: Howard, Jessica N., et al.
Published: (2024)