Copertina

Variational autoencoder-based neural network model compression

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Cheng, Liang, Guan, Peiyuan, Taherkordi, Amir, Liu, Lei, Lan, Dapeng
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Linearity-based neural network compression
di: Dobler, Silas, et al.
Pubblicazione: (2025)

LayerCollapse: Adaptive compression of neural networks
di: Shabgahi, Soheil Zibakhsh, et al.
Pubblicazione: (2023)

Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks
di: Hamreras, Safa, et al.
Pubblicazione: (2025)

Applying sparse autoencoders to unlearn knowledge in language models
di: Farrell, Eoin, et al.
Pubblicazione: (2024)

Physics-integrated generative modeling using attentive planar normalizing flow based variational autoencoder
di: Akhtar, Sheikh Waqas
Pubblicazione: (2024)

Multimodal normative modeling in Alzheimers Disease with introspective variational autoencoders
di: Kumar, Sayantan, et al.
Pubblicazione: (2026)

Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting
di: Liu, Peiyuan, et al.
Pubblicazione: (2024)

Integrating Bayesian methods with neural network--based model predictive control: a review
di: Karacelik, Asli
Pubblicazione: (2025)

Scaling and evaluating sparse autoencoders
di: Gao, Leo, et al.
Pubblicazione: (2024)

Grey-informed neural network for time-series forecasting
di: Xie, Wanli, et al.
Pubblicazione: (2024)

RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features
di: Song, Jialei, et al.
Pubblicazione: (2025)

A practical existence theorem for reduced order models based on convolutional autoencoders
di: Franco, Nicola Rares, et al.
Pubblicazione: (2024)

HCAF-DTA: drug-target binding affinity prediction with cross-attention fused hypergraph neural networks
di: Li, Jiannuo, et al.
Pubblicazione: (2025)

C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving
di: Cui, Zhihong, et al.
Pubblicazione: (2026)

MMET: A Multi-Input and Multi-Scale Transformer for Efficient PDEs Solving
di: Luo, Yichen, et al.
Pubblicazione: (2025)

A quatum inspired neural network for geometric modeling
di: Du, Weitao, et al.
Pubblicazione: (2024)

A simple connection from loss flatness to compressed neural representations
di: Chen, Shirui, et al.
Pubblicazione: (2023)

Membership Inference over Diffusion-models-based Synthetic Tabular Data
di: Cheng, Peini, et al.
Pubblicazione: (2025)

QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks
di: Jain, Naman, et al.
Pubblicazione: (2025)

Development of a graph neural network surrogate for travel demand modelling
di: Makarov, Nikita, et al.
Pubblicazione: (2024)

Explaining deep neural network models for electricity price forecasting with XAI
di: Pesenti, Antoine, et al.
Pubblicazione: (2025)

Variational decomposition autoencoding improves disentanglement of latent representations
di: Ziogas, Ioannis, et al.
Pubblicazione: (2026)

A comparative analysis of a neural network with calculated weights and a neural network with random generation of weights based on the training dataset size
di: Geidarov, Polad
Pubblicazione: (2025)

Incorporating uncertainty quantification into travel mode choice modeling: a Bayesian neural network (BNN) approach and an uncertainty-guided active survey framework
di: Zheng, Shuwen, et al.
Pubblicazione: (2024)

SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival
di: Pan, Liangrui, et al.
Pubblicazione: (2024)

Stacking-based deep neural network for player scouting in football 1
di: Lacan, Simon
Pubblicazione: (2024)

On permutation-invariant neural networks
di: Kimura, Masanari, et al.
Pubblicazione: (2024)

Sobolev acceleration for neural networks
di: Oh, Jong Kwon, et al.
Pubblicazione: (2025)

Attention mechanisms in neural networks
di: Hays, Hasi
Pubblicazione: (2026)

Principles of Lipschitz continuity in neural networks
di: Luo, Róisín
Pubblicazione: (2026)

Input Guided Multiple Deconstruction Single Reconstruction neural network models for Matrix Factorization
di: Dutta, Prasun, et al.
Pubblicazione: (2024)

SA-EMO: Structure-Aligned Encoder Mixture of Operators for Generalizable Full-waveform Inversion
di: Zhenyu, Wang, et al.
Pubblicazione: (2025)

Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks
di: Chen, Wenqian, et al.
Pubblicazione: (2024)

A constraints-based approach to fully interpretable neural networks for detecting learner behaviors
di: Pinto, Juan D., et al.
Pubblicazione: (2025)

Geometry of naturalistic object representations in recurrent neural network models of working memory
di: Lei, Xiaoxuan, et al.
Pubblicazione: (2024)

Applying graph neural network to SupplyGraph for supply chain network
di: Han, Kihwan
Pubblicazione: (2024)

On the transferability of Sparse Autoencoders for interpreting compressed models
di: Gupte, Suchit, et al.
Pubblicazione: (2025)

Implementation of tangent linear and adjoint models for neural networks based on a compiler library tool
di: Xiao, Sa, et al.
Pubblicazione: (2026)

Understanding the dynamics of the frequency bias in neural networks
di: Molina, Juan, et al.
Pubblicazione: (2024)

Graph neural networks informed locally by thermodynamics
di: Tierz, Alicia, et al.
Pubblicazione: (2024)