Cover Image

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Tianjin, Chen, Tianlong, Fang, Meng, Menkovski, Vlado, Zhao, Jiaxu, Yin, Lu, Pei, Yulong, Mocanu, Decebal Constantin, Wang, Zhangyang, Pechenizkiy, Mykola, Liu, Shiwei
Format:	Preprint
Published:	2022
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity
by: Liu, Shiwei, et al.
Published: (2021)

Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers
by: Atashgahi, Zahra, et al.
Published: (2023)

Enhancing Adversarial Training via Reweighting Optimization Trajectory
by: Huang, Tianjin, et al.
Published: (2023)

Are Sparse Neural Networks Better Hard Sample Learners?
by: Xiao, Qiao, et al.
Published: (2024)

Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution
by: Xiao, Qiao, et al.
Published: (2025)

Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
by: Wu, Boqian, et al.
Published: (2024)

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation
by: Wu, Boqian, et al.
Published: (2023)

(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork
by: Huang, Tianjin, et al.
Published: (2024)

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity
by: Xiao, Qiao, et al.
Published: (2025)

When Data Is Scarce: Scaling Sparse Language Models with Repeated Training
by: Wu, Boqian, et al.
Published: (2026)

Memory-Efficient LLM Training with Dynamic Sparsity: From Stability to Practical Scaling
by: Xiao, Qiao, et al.
Published: (2026)

NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling
by: Grooten, Bram, et al.
Published: (2025)

Unveiling the Power of Sparse Neural Networks for Feature Selection
by: Atashgahi, Zahra, et al.
Published: (2024)

Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective
by: Jin, Can, et al.
Published: (2023)

Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity
by: Muslimani, Calarina, et al.
Published: (2024)

Robust Active Learning (RoAL): Countering Dynamic Adversaries in Active Learning with Elastic Weight Consolidation
by: Fajri, Ricky Maulana, et al.
Published: (2024)

Sparse-to-Sparse Training of Diffusion Models
by: Oliveira, Inês Cardoso, et al.
Published: (2025)

Dynamic Data Pruning for Automatic Speech Recognition
by: Xiao, Qiao, et al.
Published: (2024)

On Adversarial Robustness of Language Models in Transfer Learning
by: Turbal, Bohdan, et al.
Published: (2024)

Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale
by: Timmer, Pol, et al.
Published: (2024)

Node Classification in Random Trees
by: Nuijten, Wouter W. L., et al.
Published: (2023)

Towards Fully Automated Molecular Simulations: Multi-Agent Framework for Simulation Setup and Force Field Extraction
by: Petković, Marko, et al.
Published: (2025)

SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
by: Huang, Tianjin, et al.
Published: (2025)

Aspect-Based Few-Shot Learning
by: van Engeland, Tim, et al.
Published: (2024)

Self-Regulated Neurogenesis for Online Data-Incremental Learning
by: Yildirim, Murat Onur, et al.
Published: (2024)

STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation
by: Brinke, Kiet Bennema ten, et al.
Published: (2025)

Accelerating Simulation of Two-Phase Flows with Neural PDE Surrogates
by: Poels, Yoeri, et al.
Published: (2024)

Topological degree as a discrete diagnostic for disentanglement, with applications to the $Δ$VAE
by: Ravelonanosy, Mahefa Ratsisetraina, et al.
Published: (2024)

Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
by: Minartz, Koen, et al.
Published: (2023)

PRNet: Original Information Is All You Have
by: Zheng, PeiHuang, et al.
Published: (2025)

Batch Matrix-form Equations and Implementation of Multilayer Perceptrons
by: Wesselink, Wieger, et al.
Published: (2025)

LiMTR: Time Series Motion Prediction for Diverse Road Users through Multimodal Feature Integration
by: Oerlemans, Camiel, et al.
Published: (2024)

VADA: a Data-Driven Simulator for Nanopore Sequencing
by: Niederle, Jonas, et al.
Published: (2024)

Score Matching on Large Geometric Graphs for Cosmology Generation
by: Onutu, Diana-Alexandra, et al.
Published: (2025)

HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents
by: Tomilin, Tristan, et al.
Published: (2025)

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data
by: Raes, Rik, et al.
Published: (2024)

Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
by: Provodin, Danil, et al.
Published: (2024)

FairSNA: Algorithmic Fairness in Social Network Analysis
by: Saxena, Akrati, et al.
Published: (2022)

Are There Exceptions to Goodhart's Law? On the Moral Justification of Fairness-Aware Machine Learning
by: Weerts, Hilde, et al.
Published: (2022)

Undergrads Are All You Have
by: Neth, Ashe
Published: (2024)