Gaussian Pre-Activations in Neural Networks: Myth or Reality?
Fuente:
arXiv
Saved in:
| Main Authors: | Wolinski, Pierre, Arbel, Julyan |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Gathering and Exploiting Higher-Order Information when Training Large Structured Models
by: Wolinski, Pierre
Published: (2023)
by: Wolinski, Pierre
Published: (2023)
Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit
by: Zhou, Julien, et al.
Published: (2024)
by: Zhou, Julien, et al.
Published: (2024)
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
by: Zhou, Julien, et al.
Published: (2024)
by: Zhou, Julien, et al.
Published: (2024)
Simulation-based inference of yeast centromeres
by: Touron, Eloïse, et al.
Published: (2025)
by: Touron, Eloïse, et al.
Published: (2025)
$\textit{BlockFormer}$ : Transformer-based inference from interaction maps
by: Touron, Eloïse, et al.
Published: (2026)
by: Touron, Eloïse, et al.
Published: (2026)
Error analysis of a compositional score-based algorithm for simulation-based inference
by: Touron, Camille, et al.
Published: (2025)
by: Touron, Camille, et al.
Published: (2025)
Theoretical guidelines for annealed Langevin dynamics in compositional simulation-based inference
by: Touron, Camille, et al.
Published: (2026)
by: Touron, Camille, et al.
Published: (2026)
Bounding Box Anomaly Scoring for simple and efficient Out-of-Distribution detection
by: Yahiaoui, Mohamed Bahi, et al.
Published: (2026)
by: Yahiaoui, Mohamed Bahi, et al.
Published: (2026)
An Equivalence between Bayesian Priors and Penalties in Variational Inference
by: Wolinski, Pierre, et al.
Published: (2020)
by: Wolinski, Pierre, et al.
Published: (2020)
Natural Variational Annealing for Multimodal Optimization
by: LeMinh, Tâm, et al.
Published: (2025)
by: LeMinh, Tâm, et al.
Published: (2025)
Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation
by: Rosa, Rafael Mouallem, et al.
Published: (2026)
by: Rosa, Rafael Mouallem, et al.
Published: (2026)
Learning k-Level Structured Sparse Neural Networks Using Group Envelope Regularization
by: Refael, Yehonathan, et al.
Published: (2022)
by: Refael, Yehonathan, et al.
Published: (2022)
Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms
by: Bystrova, Daria, et al.
Published: (2023)
by: Bystrova, Daria, et al.
Published: (2023)
Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes
by: Bergna, Richard, et al.
Published: (2025)
by: Bergna, Richard, et al.
Published: (2025)
Optimal sub-Gaussian variance proxy for truncated Gaussian and exponential random variables
by: Barreto, Mathias, et al.
Published: (2024)
by: Barreto, Mathias, et al.
Published: (2024)
Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations
by: Sendera, Marcin, et al.
Published: (2024)
by: Sendera, Marcin, et al.
Published: (2024)
Optimal sub-Gaussian variance proxy for 3-mass distributions
by: Atouani, Soufiane, et al.
Published: (2025)
by: Atouani, Soufiane, et al.
Published: (2025)
Region Seeding via Pre-Activation Regularization: A Geometric View of Piecewise Affine Neural Networks
by: Wei, Yi, et al.
Published: (2026)
by: Wei, Yi, et al.
Published: (2026)
Just rotate it! Uncertainty estimation in closed-source models via multiple queries
by: Pitas, Konstantinos, et al.
Published: (2024)
by: Pitas, Konstantinos, et al.
Published: (2024)
Semiring Activation in Neural Networks
by: Smets, Bart M. N., et al.
Published: (2024)
by: Smets, Bart M. N., et al.
Published: (2024)
Deep Reinforcement Learning for System-on-Chip: Myths and Realities
by: Sung, Tegg Taekyong, et al.
Published: (2022)
by: Sung, Tegg Taekyong, et al.
Published: (2022)
EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Networks
by: Arbel, Michael, et al.
Published: (2025)
by: Arbel, Michael, et al.
Published: (2025)
Learning Neural Networks with Sparse Activations
by: Awasthi, Pranjal, et al.
Published: (2024)
by: Awasthi, Pranjal, et al.
Published: (2024)
MLXP: A Framework for Conducting Replicable Experiments in Python
by: Arbel, Michael, et al.
Published: (2024)
by: Arbel, Michael, et al.
Published: (2024)
Flow Matching for Robust Simulation-Based Inference under Model Misspecification
by: Ruhlmann, Pierre-Louis, et al.
Published: (2025)
by: Ruhlmann, Pierre-Louis, et al.
Published: (2025)
Functional Bilevel Optimization for Machine Learning
by: Petrulionyte, Ieva, et al.
Published: (2024)
by: Petrulionyte, Ieva, et al.
Published: (2024)
Contextual Bandit Optimization with Pre-Trained Neural Networks
by: Terekhov, Mikhail
Published: (2025)
by: Terekhov, Mikhail
Published: (2025)
Pre-Defined Sparse Neural Networks with Hardware Acceleration
by: Dey, Sourya, et al.
Published: (2018)
by: Dey, Sourya, et al.
Published: (2018)
Seeking Interpretability and Explainability in Binary Activated Neural Networks
by: Leblanc, Benjamin, et al.
Published: (2022)
by: Leblanc, Benjamin, et al.
Published: (2022)
Deep Neural Network Initialization with Sparsity Inducing Activations
by: Price, Ilan, et al.
Published: (2024)
by: Price, Ilan, et al.
Published: (2024)
Approximation Capabilities of Feedforward Neural Networks with GELU Activations
by: Yakovlev, Konstantin, et al.
Published: (2025)
by: Yakovlev, Konstantin, et al.
Published: (2025)
1-Lipschitz Neural Networks are more expressive with N-Activations
by: Prach, Bernd, et al.
Published: (2023)
by: Prach, Bernd, et al.
Published: (2023)
Inverted Activations: Reducing Memory Footprint in Neural Network Training
by: Novikov, Georgii, et al.
Published: (2024)
by: Novikov, Georgii, et al.
Published: (2024)
Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate Networks
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
Ray-Tracing for Conditionally Activated Neural Networks
by: Gallicchio, Claudio, et al.
Published: (2025)
by: Gallicchio, Claudio, et al.
Published: (2025)
PSP: Pre-Training and Structure Prompt Tuning for Graph Neural Networks
by: Ge, Qingqing, et al.
Published: (2023)
by: Ge, Qingqing, et al.
Published: (2023)
Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
by: Dashtbayaz, Nima Hosseini, et al.
Published: (2024)
by: Dashtbayaz, Nima Hosseini, et al.
Published: (2024)
Zero-Shot Neural Network Evaluation with Sample-Wise Activation Patterns
by: Peng, Yameng, et al.
Published: (2026)
by: Peng, Yameng, et al.
Published: (2026)
Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks
by: Chen, Wenlin, et al.
Published: (2023)
by: Chen, Wenlin, et al.
Published: (2023)
Extension of Symmetrized Neural Network Operators with Fractional and Mixed Activation Functions
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025)
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025)
Similar Items
-
Gathering and Exploiting Higher-Order Information when Training Large Structured Models
by: Wolinski, Pierre
Published: (2023) -
Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit
by: Zhou, Julien, et al.
Published: (2024) -
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
by: Zhou, Julien, et al.
Published: (2024) -
Simulation-based inference of yeast centromeres
by: Touron, Eloïse, et al.
Published: (2025) -
$\textit{BlockFormer}$ : Transformer-based inference from interaction maps
by: Touron, Eloïse, et al.
Published: (2026)