Saved in:
| Main Authors: | Origer, Sebastien, Izzo, Dario |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.18084 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Closing the gap: Optimizing Guidance and Control Networks through Neural ODEs
by: Origer, Sebastien, et al.
Published: (2024)
by: Origer, Sebastien, et al.
Published: (2024)
Comparing Behavioural Cloning and Reinforcement Learning for Spacecraft Guidance and Control Networks
by: Holt, Harry, et al.
Published: (2025)
by: Holt, Harry, et al.
Published: (2025)
Certifying Guidance & Control Networks: Uncertainty Propagation to an Event Manifold
by: Origer, Sebastien, et al.
Published: (2024)
by: Origer, Sebastien, et al.
Published: (2024)
High-order expansion of Neural Ordinary Differential Equations flows
by: Izzo, Dario, et al.
Published: (2025)
by: Izzo, Dario, et al.
Published: (2025)
Optimality Principles in Spacecraft Neural Guidance and Control
by: Izzo, Dario, et al.
Published: (2023)
by: Izzo, Dario, et al.
Published: (2023)
Learning the optimal state-feedback via supervised imitation learning
by: Tailor, Dharmesh, et al.
Published: (2019)
by: Tailor, Dharmesh, et al.
Published: (2019)
MasconCube: Fast and Accurate Gravity Modeling with an Explicit Representation
by: Fanti, Pietro, et al.
Published: (2025)
by: Fanti, Pietro, et al.
Published: (2025)
EclipseNETs: a differentiable description of irregular eclipse conditions
by: Acciarini, Giacomo, et al.
Published: (2024)
by: Acciarini, Giacomo, et al.
Published: (2024)
Closing the Gap Between SGP4 and High-Precision Propagation via Differentiable Programming
by: Acciarini, Giacomo, et al.
Published: (2024)
by: Acciarini, Giacomo, et al.
Published: (2024)
Computing low-thrust transfers in the asteroid belt, a comparison between astrodynamical manipulations and a machine learning approach
by: Acciarini, Giacomo, et al.
Published: (2024)
by: Acciarini, Giacomo, et al.
Published: (2024)
NeuralODEs for VLEO simulations: Introducing thermoNET for Thermosphere Modeling
by: Izzo, Dario, et al.
Published: (2024)
by: Izzo, Dario, et al.
Published: (2024)
EclipseNETs: Learning Irregular Small Celestial Body Silhouettes
by: Acciarini, Giacomo, et al.
Published: (2025)
by: Acciarini, Giacomo, et al.
Published: (2025)
Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate Networks
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
Subtractive Modulative Network with Learnable Periodic Activations
by: Wang, Tiou, et al.
Published: (2026)
by: Wang, Tiou, et al.
Published: (2026)
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
by: Mavor-Parker, Augustine N., et al.
Published: (2024)
by: Mavor-Parker, Augustine N., et al.
Published: (2024)
Pretrained Approximators for Low-Thrust Trajectory Cost and Reachability
by: Zhang, Zhong, et al.
Published: (2026)
by: Zhang, Zhong, et al.
Published: (2026)
Activation Functions Considered Harmful: Recovering Neural Network Weights through Controlled Channels
by: Spielman, Jesse, et al.
Published: (2025)
by: Spielman, Jesse, et al.
Published: (2025)
Subgroup Discovery with the Cox Model
by: Izzo, Zachary, et al.
Published: (2025)
by: Izzo, Zachary, et al.
Published: (2025)
Semi-Periodic Activation for Time Series Classification
by: Júnior, José Gilberto Barbosa de Medeiros, et al.
Published: (2024)
by: Júnior, José Gilberto Barbosa de Medeiros, et al.
Published: (2024)
Combinations of Fast Activation and Trigonometric Functions in Kolmogorov-Arnold Networks
by: Ta, Hoang-Thang, et al.
Published: (2025)
by: Ta, Hoang-Thang, et al.
Published: (2025)
Efficient Verification of Neural Control Barrier Functions with Smooth Nonlinear Activations
by: Zhang, Jun, et al.
Published: (2026)
by: Zhang, Jun, et al.
Published: (2026)
Topology-Aware Activation Functions in Neural Networks
by: Snopov, Pavel, et al.
Published: (2025)
by: Snopov, Pavel, et al.
Published: (2025)
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)
Deep Network Approximation: Beyond ReLU to Diverse Activation Functions
by: Zhang, Shijun, et al.
Published: (2023)
by: Zhang, Shijun, et al.
Published: (2023)
Quantitative Bounds for Length Generalization in Transformers
by: Izzo, Zachary, et al.
Published: (2025)
by: Izzo, Zachary, et al.
Published: (2025)
Comprehensive Survey of Complex-Valued Neural Networks: Insights into Backpropagation and Activation Functions
by: Hammad, M. M.
Published: (2024)
by: Hammad, M. M.
Published: (2024)
Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networks
by: Jiang, Jiun-Cheng, et al.
Published: (2025)
by: Jiang, Jiun-Cheng, et al.
Published: (2025)
Adaptive Diffusion Guidance via Stochastic Optimal Control
by: Azangulov, Iskander, et al.
Published: (2025)
by: Azangulov, Iskander, et al.
Published: (2025)
Spectral Guidance for Flexible and Efficient Control of Diffusion Models
by: Moreira, Gabriel, et al.
Published: (2026)
by: Moreira, Gabriel, et al.
Published: (2026)
Diffusion Guidance Is a Controllable Policy Improvement Operator
by: Frans, Kevin, et al.
Published: (2025)
by: Frans, Kevin, et al.
Published: (2025)
Policy Gradient Guidance Enables Test Time Control
by: Qi, Jianing, et al.
Published: (2025)
by: Qi, Jianing, et al.
Published: (2025)
Neural Functions for Learning Periodic Signal
by: Cho, Woojin, et al.
Published: (2025)
by: Cho, Woojin, et al.
Published: (2025)
Fractional Concepts in Neural Networks: Enhancing Activation Functions
by: Alijani, Zahra, et al.
Published: (2023)
by: Alijani, Zahra, et al.
Published: (2023)
Beyond Lipschitz Continuity and Monotonicity: Fractal and Chaotic Activation Functions in Echo State Networks
by: Chipera, Rae, et al.
Published: (2025)
by: Chipera, Rae, et al.
Published: (2025)
Activation Functions for "A Feedforward Unitary Equivariant Neural Network"
by: Ma, Pui-Wai
Published: (2024)
by: Ma, Pui-Wai
Published: (2024)
One Period to Rule Them All: Identifying Critical Learning Periods in Deep Networks
by: Fukase, Vinicius Yuiti, et al.
Published: (2025)
by: Fukase, Vinicius Yuiti, et al.
Published: (2025)
Switchable Activation Networks
by: Ale, Laha, et al.
Published: (2026)
by: Ale, Laha, et al.
Published: (2026)
Provably Reliable Classifier Guidance via Cross-Entropy Control
by: Sahu, Sharan, et al.
Published: (2026)
by: Sahu, Sharan, et al.
Published: (2026)
ULU: A Unified Activation Function
by: Huo, Simin
Published: (2025)
by: Huo, Simin
Published: (2025)
Guidance and Control Neural Network Acceleration using Memristors
by: Rudge, Zacharia A., et al.
Published: (2025)
by: Rudge, Zacharia A., et al.
Published: (2025)
Similar Items
-
Closing the gap: Optimizing Guidance and Control Networks through Neural ODEs
by: Origer, Sebastien, et al.
Published: (2024) -
Comparing Behavioural Cloning and Reinforcement Learning for Spacecraft Guidance and Control Networks
by: Holt, Harry, et al.
Published: (2025) -
Certifying Guidance & Control Networks: Uncertainty Propagation to an Event Manifold
by: Origer, Sebastien, et al.
Published: (2024) -
High-order expansion of Neural Ordinary Differential Equations flows
by: Izzo, Dario, et al.
Published: (2025) -
Optimality Principles in Spacecraft Neural Guidance and Control
by: Izzo, Dario, et al.
Published: (2023)