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The Principles of Deep Learning Theory

The Principles of Deep Learning Theory

Daniel A. Roberts
Sho Yaida
Boris Hanin
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Papers citing "The Principles of Deep Learning Theory"

6 / 6 papers shown
Title
Plane-Wave Decomposition and Randomised Training; a Novel Path to Generalised PINNs for SHM
Plane-Wave Decomposition and Randomised Training; a Novel Path to Generalised PINNs for SHM
Rory Clements
James Ellis
Geoff Hassall
Simon Horsley
Gavin Tabor
71
0
0
31 Mar 2025
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Dayal Singh Kalra
Tianyu He
M. Barkeshli
86
4
0
17 Feb 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Blake Bordelon
Cengiz Pehlevan
AI4CE
111
1
0
04 Feb 2025
Merino: Entropy-driven Design for Generative Language Models on IoT Devices
Merino: Entropy-driven Design for Generative Language Models on IoT Devices
Youpeng Zhao
Ming Lin
Huadong Tang
Qiang Wu
Jun Wang
98
0
0
28 Jan 2025
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model
F.S. Pezzicoli
V. Ros
F.P. Landes
M. Baity-Jesi
52
2
0
20 Jan 2025
Bayesian RG Flow in Neural Network Field Theories
Bayesian RG Flow in Neural Network Field Theories
Jessica N. Howard
Marc S. Klinger
Anindita Maiti
A. G. Stapleton
75
1
0
27 May 2024