Generative flow induced neural architecture search: Towards discovering optimal architecture in wavelet neural operator

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Soin, Hartej, Tripura, Tapas, Chakraborty, Souvik
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative adversarial wavelet neural operator: Application to fault detection and isolation of multivariate time series data
by: Rani, Jyoti, et al.
Published: (2024)

From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems
by: Kumar, Sawan, et al.
Published: (2025)

Global optimization of graph acquisition functions for neural architecture search
by: Xie, Yilin, et al.
Published: (2025)

Additive regularization schedule for neural architecture search
by: Potanin, Mark, et al.
Published: (2024)

Deep Muscle EMG construction using A Physics-Integrated Deep Learning approach
by: Kumar, Rajnish, et al.
Published: (2025)

Chain-structured neural architecture search for financial time series forecasting
by: Levchenko, Denis, et al.
Published: (2024)

Spatio-spectral graph neural operator for solving computational mechanics problems on irregular domain and unstructured grid
by: Sarkar, Subhankar, et al.
Published: (2024)

Physics- and geometry-aware spatio-spectral graph neural operator for time-independent and time-dependent PDEs
by: Sarkar, Subhankar, et al.
Published: (2025)

Differentiable architecture search with multi-dimensional attention for spiking neural networks
by: Man, Yilei, et al.
Published: (2024)

Graph is all you need? Lightweight data-agnostic neural architecture search without training
by: Huang, Zhenhan, et al.
Published: (2024)

An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters
by: Keisler, Julie, et al.
Published: (2023)

Growth strategies for arbitrary DAG neural architectures
by: Douka, Stella, et al.
Published: (2025)

Automatic selection of the best neural architecture for time series forecasting
by: Cao, Qianying, et al.
Published: (2025)

Characterization of topological structures in different neural network architectures
by: Świder, Paweł
Published: (2024)

A framework for measuring the training efficiency of a neural architecture
by: Cueto-Mendoza, Eduardo, et al.
Published: (2024)

Topological derivative approach for deep neural network architecture adaptation
by: Krishnanunni, C G, et al.
Published: (2025)

Restricting to the chip architecture maintains the quantum neural network accuracy
by: Friedrich, Lucas, et al.
Published: (2022)

Separable neural architectures as a primitive for unified predictive and generative intelligence
by: Batley, Reza T., et al.
Published: (2026)

Quantum feedback control with a transformer neural network architecture
by: Vaidhyanathan, Pranav, et al.
Published: (2024)

Neuromorphic on-chip reservoir computing with spiking neural network architectures
by: Karki, Samip, et al.
Published: (2024)

Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation law
by: Zhang, Jingdong, et al.
Published: (2024)

Domain decomposition architectures and Gauss-Newton training for physics-informed neural networks
by: Heinlein, Alexander, et al.
Published: (2025)

Model selection in hybrid quantum neural networks with applications to quantum transformer architectures
by: Wadhwa, Harsh, et al.
Published: (2026)

Towards Gaussian Process for operator learning: an uncertainty aware resolution independent operator learning algorithm for computational mechanics
by: Kumar, Sawan, et al.
Published: (2024)

Hybrid variable spiking graph neural networks for energy-efficient scientific machine learning
by: Jain, Isha, et al.
Published: (2024)

Provable wavelet-based neural approximation
by: Hur, Youngmi, et al.
Published: (2025)

Drought forecasting using a hybrid neural architecture for integrating time series and static data
by: Agudelo, Julian, et al.
Published: (2025)

Gated recurrent neural networks discover attention
by: Zucchet, Nicolas, et al.
Published: (2023)

Comparative analysis of neural network architectures for short-term FOREX forecasting
by: Zafeiriou, Theodoros, et al.
Published: (2024)

Lipschitz constant estimation for general neural network architectures using control tools
by: Pauli, Patricia, et al.
Published: (2024)

Distribution free uncertainty quantification in neuroscience-inspired deep operators
by: Garg, Shailesh, et al.
Published: (2024)

Event-driven physics-informed operator learning for reliability analysis
by: Garg, Shailesh, et al.
Published: (2025)

The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems
by: Biazzo, Indaco
Published: (2023)

Data-driven discovery of interpretable Lagrangian of stochastically excited dynamical systems
by: Tripura, Tapas, et al.
Published: (2024)

Reinforcement learning-based architecture search for quantum machine learning
by: Rapp, Frederic, et al.
Published: (2024)

Network architecture search of X-ray based scientific applications
by: Balaji, Adarsha, et al.
Published: (2024)

Koopman operator for time-dependent reliability analysis
by: N., Navaneeth, et al.
Published: (2022)

A logical re-conception of neural networks: Hamiltonian bitwise part-whole architecture
by: Bowen, E, et al.
Published: (2026)

An efficient wavelet-based physics-informed neural network for multiscale problems
by: Pandey, Himanshu, et al.
Published: (2024)

Ranking‐based architecture generation for surrogate‐assisted neural architecture search
by: Songyi Xiao, et al.
Published: (2024)