mlsanityData to 7 Oct 2026

Guidance and Control Networks with Periodic Activation Functions

arXiv 2405.18084 ↗First posted 28 May 2024cs.LGcited by 7

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Abstract (arXiv)

Inspired by the versatility of sinusoidal representation networks (SIRENs), we present a modified Guidance & Control Networks (G&CNETs) variant using periodic activation functions in the hidden layers. We demonstrate that the resulting G&CNETs train faster and achieve a lower overall training error on three different control scenarios on which G&CNETs have been tested previously. A preliminary analysis is presented in an attempt to explain the superior performance of the SIREN architecture for the particular types of tasks that G&CNETs excel on.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 10 of its 24 references that are in the map. First posted on arXiv 28 May 2024.

Builds on

10 of 24 references.

References · 10

  1. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,590
  2. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,214
  3. 2019Real-Time Optimal Control for Irregular Asteroid Landings Using Deep Neural Networkscited by 11
  4. 2018On the stability analysis of deep neural network representations of an optimal state-feedbackcited by 10
  5. 2022Neural representation of a time optimal, constant acceleration rendezvouscited by 10
  6. 2019Aggressive Online Control of a Quadrotor via Deep Network Representations of Optimality Principlescited by 9
  7. 2023End-to-end Neural Network Based Quadcopter controlcited by 9
  8. 2016Deep Neural Networks for Improved, Impromptu Trajectory Tracking of Quadrotorscited by 7
  9. 2023Guidance & Control Networks for Time-Optimal Quadcopter Flightcited by 6
  10. 2023Optimality Principles in Spacecraft Neural Guidance and Controlcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 1.

7 papers.

  1. 2024SineKAN: Kolmogorov-Arnold Networks Using Sinusoidal Activation Functionscited by 15
  2. 2024Certifying Guidance & Control Networks: Uncertainty Propagation to an Event Manifoldcited by 1
  3. 2025High-order expansion of Neural Ordinary Differential Equations flowscited by 1
  4. 2025Memristor-Based Neural Network Accelerators for Space Applications: Enhancing Performance with Temporal Averaging and SIRENscited by 1
  5. 2025Comparing Behavioural Cloning and Reinforcement Learning for Spacecraft Guidance and Control Networkscited by 0
  6. 2025Reconfiguration of pivoting cube ensembles under local sensing constraints using geometric deep learningcited by 0
  7. 2026Sample-Free Safety Assessment of Neural Network Controllers via Taylor Methodscited by 0