Saved in:
| Main Authors: | Bone, Viv, van der Heide, Chris, Mackle, Kieran, Jahn, Ingo H. J., Dower, Peter M., Manzie, Chris |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.16059 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Hamilton-Jacobi-Bellman Approach to Ellipsoidal Approximations of Reachable Sets for Linear Time-Varying Systems
by: Liu, Vincent, et al.
Published: (2024)
by: Liu, Vincent, et al.
Published: (2024)
Upper and Lower Bounds for a Class of Constrained Linear Time-Varying Games
by: Liu, Vincent, et al.
Published: (2025)
by: Liu, Vincent, et al.
Published: (2025)
Is the Last Layer Sufficient for Uncertainty Quantification?
by: Wilson, Joseph, et al.
Published: (2026)
by: Wilson, Joseph, et al.
Published: (2026)
Uncertainty Quantification with the Empirical Neural Tangent Kernel
by: Wilson, Joseph, et al.
Published: (2025)
by: Wilson, Joseph, et al.
Published: (2025)
Temperature Optimization for Bayesian Deep Learning
by: Ng, Kenyon, et al.
Published: (2024)
by: Ng, Kenyon, et al.
Published: (2024)
Spectral Estimation with Free Decompression
by: Ameli, Siavash, et al.
Published: (2025)
by: Ameli, Siavash, et al.
Published: (2025)
Free Decompression with Algebraic Spectral Curves
by: Ameli, Siavash, et al.
Published: (2026)
by: Ameli, Siavash, et al.
Published: (2026)
The Interpolating Information Criterion for Overparameterized Models
by: Hodgkinson, Liam, et al.
Published: (2023)
by: Hodgkinson, Liam, et al.
Published: (2023)
Determinant Estimation under Memory Constraints and Neural Scaling Laws
by: Ameli, Siavash, et al.
Published: (2025)
by: Ameli, Siavash, et al.
Published: (2025)
GMM-Based Time-Varying Coverage Control
by: Zamani, Behzad, et al.
Published: (2025)
by: Zamani, Behzad, et al.
Published: (2025)
Transfer learning for multifidelity simulation-based inference in cosmology
by: Saoulis, Alex A., et al.
Published: (2025)
by: Saoulis, Alex A., et al.
Published: (2025)
Discretization-independent multifidelity operator learning for partial differential equations
by: Hauck, Jacob, et al.
Published: (2025)
by: Hauck, Jacob, et al.
Published: (2025)
A multifidelity approach to continual learning for physical systems
by: Howard, Amanda, et al.
Published: (2023)
by: Howard, Amanda, et al.
Published: (2023)
MF-GLaM: A multifidelity stochastic emulator using generalized lambda models
by: Giannoukou, K., et al.
Published: (2025)
by: Giannoukou, K., et al.
Published: (2025)
Auditing Information Disclosure During LLM-Scale Gradient Descent Using Gradient Uniqueness
by: Abdelghafar, Sleem, et al.
Published: (2025)
by: Abdelghafar, Sleem, et al.
Published: (2025)
Bidirectional Adversarial Autoencoders for the design of Plasmonic Metasurfaces
by: Liu, Yuansan, et al.
Published: (2024)
by: Liu, Yuansan, et al.
Published: (2024)
High-Dimensional Gaussian Process Regression with Soft Kernel Interpolation
by: Camaño, Chris, et al.
Published: (2024)
by: Camaño, Chris, et al.
Published: (2024)
Training Without Orthogonalization, Inference With SVD: A Gradient Analysis of Rotation Representations
by: Choy, Chris
Published: (2026)
by: Choy, Chris
Published: (2026)
A curated UK rain radar data set for training and benchmarking nowcasting models
by: Atureta, Viv, et al.
Published: (2025)
by: Atureta, Viv, et al.
Published: (2025)
Universal approximation with complex-valued deep narrow neural networks
by: Geuchen, Paul, et al.
Published: (2023)
by: Geuchen, Paul, et al.
Published: (2023)
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
by: Carmona, Chris U., et al.
Published: (2020)
by: Carmona, Chris U., et al.
Published: (2020)
Projection-based multifidelity linear regression for data-scarce applications
by: Sella, Vignesh, et al.
Published: (2025)
by: Sella, Vignesh, et al.
Published: (2025)
Fast Decentralized Gradient Tracking for Federated Minimax Optimization with Local Updates
by: Li, Chris Junchi
Published: (2024)
by: Li, Chris Junchi
Published: (2024)
DTI-GP: Bayesian operations for drug-target interactions using deep kernel Gaussian processes
by: Bolgár, Bence, et al.
Published: (2025)
by: Bolgár, Bence, et al.
Published: (2025)
GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications
by: Morrison, Oisín M., et al.
Published: (2024)
by: Morrison, Oisín M., et al.
Published: (2024)
Bridging quantum and classical computing for partial differential equations through multifidelity machine learning
by: Jacob, Bruno, et al.
Published: (2025)
by: Jacob, Bruno, et al.
Published: (2025)
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
by: Cundy, Chris, et al.
Published: (2020)
by: Cundy, Chris, et al.
Published: (2020)
Deciphering diffuse scattering with machine learning and the equivariant foundation model: The case of molten FeO
by: Sivaraman, Ganesh, et al.
Published: (2024)
by: Sivaraman, Ganesh, et al.
Published: (2024)
Detecting and measuring respiratory events in horses during exercise with a microphone: deep learning vs. standard signal processing
by: Parmentier, Jeanne I. M., et al.
Published: (2025)
by: Parmentier, Jeanne I. M., et al.
Published: (2025)
Learning in Deep Factor Graphs with Gaussian Belief Propagation
by: Nabarro, Seth, et al.
Published: (2023)
by: Nabarro, Seth, et al.
Published: (2023)
Gradient GA: Gradient Genetic Algorithm for Drug Molecular Design
by: Zhuang, Chris, et al.
Published: (2025)
by: Zhuang, Chris, et al.
Published: (2025)
Deep Gaussian Process Proximal Policy Optimization
by: van der Lende, Matthijs, et al.
Published: (2025)
by: van der Lende, Matthijs, et al.
Published: (2025)
Gradient descent for deep equilibrium single-index models
by: Dandapanthula, Sanjit, et al.
Published: (2025)
by: Dandapanthula, Sanjit, et al.
Published: (2025)
Learning When to Switch: Adaptive Policy Selection via Reinforcement Learning
by: Tava, Chris
Published: (2025)
by: Tava, Chris
Published: (2025)
An elementary proof of a universal approximation theorem
by: Monico, Chris
Published: (2024)
by: Monico, Chris
Published: (2024)
RFX-Fuse: Breiman and Cutler's Unified ML Engine + Native Explainable Similarity
by: Kuchar, Chris
Published: (2026)
by: Kuchar, Chris
Published: (2026)
Deep Reinforcement Learning for Autonomous Cyber Defence: A Survey
by: Palmer, Gregory, et al.
Published: (2023)
by: Palmer, Gregory, et al.
Published: (2023)
Bias Leaves a Gradient Trail: Label-Free Bias Identification via Gradient Probes on Concept Decompositions
by: Vitry, Thomas, et al.
Published: (2026)
by: Vitry, Thomas, et al.
Published: (2026)
A Distributed Gaussian Process Model for Multi-Robot Mapping
by: Nabarro, Seth, et al.
Published: (2026)
by: Nabarro, Seth, et al.
Published: (2026)
Quantitative mapping from conventional MRI using self-supervised physics-guided deep learning: applications to a large-scale, clinically heterogeneous dataset
by: van Lune, Jelmer, et al.
Published: (2026)
by: van Lune, Jelmer, et al.
Published: (2026)
Similar Items
-
A Hamilton-Jacobi-Bellman Approach to Ellipsoidal Approximations of Reachable Sets for Linear Time-Varying Systems
by: Liu, Vincent, et al.
Published: (2024) -
Upper and Lower Bounds for a Class of Constrained Linear Time-Varying Games
by: Liu, Vincent, et al.
Published: (2025) -
Is the Last Layer Sufficient for Uncertainty Quantification?
by: Wilson, Joseph, et al.
Published: (2026) -
Uncertainty Quantification with the Empirical Neural Tangent Kernel
by: Wilson, Joseph, et al.
Published: (2025) -
Temperature Optimization for Bayesian Deep Learning
by: Ng, Kenyon, et al.
Published: (2024)