Virtual neural networks: hundreds of souls in a body

arXiv:2609.24782 · cs.CV · Submitted 2026-09-21 · Read on arXiv

cs.CV

Submitted: 2026-09-21

Updated: 2026-09-21

Terminology

• Accuracy — 36× in this paper · explained in 1 episode
• Aggregation — 14× in this paper · explained in 1 episode
• Loss Function — 7× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Aggregation Function — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Latent Representation — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Virtual Neural Networks Ensemble — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Cooperation — 2× in this paper · explained in 2 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Pruning — 2× in this paper · explained in 4 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Monte Carlo dropout — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
• Generalized Negative Correlation Learning for Deep Ensembling
• Averaging Weights Leads to Wider Optima and Better Generalization
• Stochastic Weight Averaging in Parallel: Large-Batch Training that Generalizes Well
• Snapshot Ensembles: Train 1, get M for free
• SGDR: Stochastic Gradient Descent with Warm Restarts
• Training independent subnetworks for robust prediction
• Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity
• Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
• BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning
• Unsupervised Neural Machine Translation with Weight Sharing
• Adam: A Method for Stochastic Optimization
• The Efficiency Misnomer

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