Compositional modeling of nonlinear dynamical systems with ODE-based random features T McDonald, M Álvarez Advances in Neural Information Processing Systems 34, 13809-13819, 2021 | 14 | 2021 |
The University of Sheffield at CheckThat! 2020: Claim Identification and Verification on Twitter. TM McDonald, ZQ Dong, Y Zhang, R Hampson, J Young, Q Cao, ... CLEF (Working Notes), 2020 | 14 | 2020 |
Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay TM McDonald, L Maystre, M Lalmas, D Russo, K Ciosek Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 9 | 2023 |
Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning T Baldwin-McDonald, MA Álvarez arXiv preprint arXiv:2311.14828, 2023 | 1 | 2023 |
Nonparametric Gaussian Process Covariances via Multidimensional Convolutions TM McDonald, M Ross, MT Smith, MA Álvarez International Conference on Artificial Intelligence and Statistics, 8279-8293, 2023 | 1 | 2023 |
Shallow and Deep Nonparametric Convolutions for Gaussian Processes TM McDonald, M Ross, MT Smith, MA Álvarez arXiv preprint arXiv:2206.08972, 2022 | 1 | 2022 |
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models X Shi, T Baldwin-McDonald, MA Álvarez arXiv preprint arXiv:2407.01856, 2024 | | 2024 |
Bayesian Uncertainty Estimation in Landmark Localization Using Convolutional Gaussian Processes L Schobs, TM McDonald, H Lu International Workshop on Uncertainty for Safe Utilization of Machine …, 2023 | | 2023 |
One-shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian Manifolds. S Pathak, TM McDonald, R Penne CoRR, 2023 | | 2023 |