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Christopher van der Heide
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2020 – today
- 2025
- [j1]Viv Bone, Chris van der Heide, Kieran Mackle, Ingo Jahn, Peter M. Dower, Chris Manzie:
Gradient-enhanced deep Gaussian processes for multifidelity modeling. J. Comput. Phys. 520: 113474 (2025) - [i9]Joseph Wilson, Chris van der Heide, Liam Hodgkinson, Fred Roosta:
Uncertainty Quantification with the Empirical Neural Tangent Kernel. CoRR abs/2502.02870 (2025) - [i8]Siavash Ameli, Chris van der Heide, Liam Hodgkinson, Fred Roosta, Michael W. Mahoney:
Determinant Estimation under Memory Constraints and Neural Scaling Laws. CoRR abs/2503.04424 (2025) - 2024
- [i7]Viv Bone, Chris van der Heide, Kieran Mackle, Ingo H. J. Jahn, Peter M. Dower, Chris Manzie:
Gradient-enhanced deep Gaussian processes for multifidelity modelling. CoRR abs/2402.16059 (2024) - [i6]Kenyon Ng, Chris van der Heide, Liam Hodgkinson, Susan Wei:
Temperature Optimization for Bayesian Deep Learning. CoRR abs/2410.05757 (2024) - 2023
- [c5]Chris van der Heide, Peter Cudmore, Ingo Jahn, Viv Bone, Peter M. Dower, Chris Manzie:
Feasibility Detection for Nested Codesign of Hypersonic Vehicles. CDC 2023: 632-637 - [c4]Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney:
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes. ICML 2023: 13085-13117 - [i5]Liam Hodgkinson, Christopher van der Heide, Robert Salomone, Fred Roosta, Michael W. Mahoney:
The Interpolating Information Criterion for Overparameterized Models. CoRR abs/2307.07785 (2023) - [i4]Liam Hodgkinson, Christopher van der Heide, Robert Salomone, Fred Roosta, Michael W. Mahoney:
A PAC-Bayesian Perspective on the Interpolating Information Criterion. CoRR abs/2311.07013 (2023) - 2022
- [i3]Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney:
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes. CoRR abs/2210.07612 (2022) - 2021
- [c3]Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher
:
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. AAAI 2021: 9967-9977 - [c2]Christopher van der Heide, Fred Roosta, Liam Hodgkinson, Dirk P. Kroese:
Shadow Manifold Hamiltonian Monte Carlo. AISTATS 2021: 1477-1485 - [c1]Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney:
Stochastic continuous normalizing flows: training SDEs as ODEs. UAI 2021: 1130-1140 - 2020
- [i2]Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher:
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. CoRR abs/2002.08517 (2020) - [i1]Liam Hodgkinson, Christopher van der Heide, Fred Roosta, Michael W. Mahoney:
Stochastic Normalizing Flows. CoRR abs/2002.09547 (2020)
Coauthor Index
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