Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details

arXiv:2108.11000 · stat.ML, cs.LG · Submitted 2021-08-25 · Read on arXiv

stat.ML, cs.LG

Submitted: 2021-08-25

Updated: 2022-07-08

Journal ref: Neural Networks 167 (2023): 309-330

DOI: 10.1016/j.neunet.2023.08.029

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Sparsity — 45× in this paper · explained in 4 episodes
• Accuracy — 23× in this paper · explained in 1 episode
• Pruning — 17× in this paper · explained in 4 episodes
• Consistency — 13× in this paper · explained in 3 episodes
• Variational Bayes — 8× in this paper · explained in 2 episodes
• Adam — 7× in this paper · explained in 2 episodes
• Activation Function — 5× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Theoretical Guarantees — 3× in this paper · explained in 2 episodes
• Markov Chain Monte Carlo — 2× in this paper
• Federated Learning — 1× in this paper · explained in 15 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Stochastic Dynamics — 1× in this paper · explained in 2 episodes

Sources

• Searching for Activation Functions

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