Imagen de Portada

Neural Surveillance: Live-Update Visualization of Latent Training Dynamics

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Yang, Xianglin, Dong, Jin Song
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Gradient Flow Matching for Learning Update Dynamics in Neural Network Training
por: Shou, Xiao, et al.
Publicado: (2025)

Turning Bias into Bugs: Bandit-Guided Style Manipulation Attacks on LLM Judges
por: Yang, Xianglin, et al.
Publicado: (2026)

Latent State Models of Training Dynamics
por: Hu, Michael Y., et al.
Publicado: (2023)

Langevin Flows for Modeling Neural Latent Dynamics
por: Song, Yue, et al.
Publicado: (2025)

A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs
por: Yang, Sikun, et al.
Publicado: (2023)

Navigating the Latent Space Dynamics of Neural Models
por: Fumero, Marco, et al.
Publicado: (2025)

Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics
por: Chen, Yenho, et al.
Publicado: (2024)

Stochastic and Non-local Closure Modeling for Nonlinear Dynamical Systems via Latent Score-based Generative Models
por: Dong, Xinghao, et al.
Publicado: (2025)

Latent Field Discovery In Interacting Dynamical Systems With Neural Fields
por: Kofinas, Miltiadis, et al.
Publicado: (2023)

Ignoring Directionality Leads to Compromised Graph Neural Network Explanations
por: Sun, Changsheng, et al.
Publicado: (2025)

Geometric Neural Operators via Lie Group-Constrained Latent Dynamics
por: Zhang, Jiaquan, et al.
Publicado: (2026)

SWAT-NN: Simultaneous Weights and Architecture Training for Neural Networks in a Latent Space
por: Huang, Zitong, et al.
Publicado: (2025)

Coupled Transformer Autoencoder for Disentangling Multi-Region Neural Latent Dynamics
por: Sristi, Ram Dyuthi, et al.
Publicado: (2025)

How Graph Neural Networks Learn: Lessons from Training Dynamics
por: Yang, Chenxiao, et al.
Publicado: (2023)

Rich-Observation Reinforcement Learning with Continuous Latent Dynamics
por: Song, Yuda, et al.
Publicado: (2024)

Latent Space Energy-based Neural ODEs
por: Cheng, Sheng, et al.
Publicado: (2024)

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators
por: Li, Shanda, et al.
Publicado: (2025)

Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems
por: Hu, Amber, et al.
Publicado: (2024)

MuCon: Clipped Muon Updates for LLM Training
por: Yi, Albert
Publicado: (2026)

Exploring the Impact of Parameter Update Magnitude on Forgetting and Generalization of Continual Learning
por: He, JinLi, et al.
Publicado: (2026)

Visual Latents Know More Than They Say: Unsilencing Latent Reasoning in MLLMs
por: Zhang, Xin, et al.
Publicado: (2026)

Clustering Head: A Visual Case Study of the Training Dynamics in Transformers
por: Odonnat, Ambroise, et al.
Publicado: (2024)

Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training
por: Xie, Jiancheng, et al.
Publicado: (2024)

Dynamic Rank Adjustment for Accurate and Efficient Neural Network Training
por: Shin, Hyuntak, et al.
Publicado: (2025)

Using Neural Implicit Flow To Represent Latent Dynamics Of Canonical Systems
por: Nasim, Imran, et al.
Publicado: (2024)

Generative Modeling of Neural Dynamics via Latent Stochastic Differential Equations
por: ElGazzar, Ahmed, et al.
Publicado: (2024)

Shared Latent Space by Both Languages in Non-Autoregressive Neural Machine Translation
por: Heo, DongNyeong, et al.
Publicado: (2023)

$ε$-rank and the Staircase Phenomenon: New Insights into Neural Network Training Dynamics
por: Yang, Jiang, et al.
Publicado: (2024)

Synergizing Transport-Based Generative Models and Latent Geometry for Stochastic Closure Modeling
por: Dong, Xinghao, et al.
Publicado: (2026)

Partial Parameter Updates for Efficient Distributed Training
por: Filippova, Anastasiia, et al.
Publicado: (2025)

ElfCore: A 28nm Neural Processor Enabling Dynamic Structured Sparse Training and Online Self-Supervised Learning with Activity-Dependent Weight Update
por: Su, Zhe, et al.
Publicado: (2025)

Dynamic Latent Separation for Deep Learning
por: Tuan, Yi-Lin, et al.
Publicado: (2022)

Quantifying Emergence in Neural Networks: Insights from Pruning and Training Dynamics
por: AlShinaifi, Faisal, et al.
Publicado: (2024)

Lightweight Auto-bidding based on Traffic Prediction in Live Advertising
por: Yang, Bo, et al.
Publicado: (2025)

ELVIS: Ensemble-Calibrated Latent Imagination for Long-Horizon Visual MPC
por: Du, Yurui, et al.
Publicado: (2026)

Training Latent Diffusion Models with Interacting Particle Algorithms
por: Wang, Tim Y. J., et al.
Publicado: (2025)

Learning Latent Space Dynamics with Model-Form Uncertainties: A Stochastic Reduced-Order Modeling Approach
por: Yong, Jin Yi, et al.
Publicado: (2024)

Selective Task Group Updates for Multi-Task Optimization
por: Jeong, Wooseong, et al.
Publicado: (2025)

How Neural Losses Shape VAE Latents
por: Strano, Giorgio, et al.
Publicado: (2026)

Latent Space Representations of Neural Algorithmic Reasoners
por: Mirjanić, Vladimir V., et al.
Publicado: (2023)