Oberhauser, Harald

13 publications

AISTATS 2025 Learning to Forget: Bayesian Time Series Forecasting Using Recurrent Sparse Spectrum Signature Gaussian Processes Csaba Tóth, Masaki Adachi, Michael A Osborne, Harald Oberhauser

AISTATS 2024 Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne

NeurIPS 2023 Kernelized Cumulants: Beyond Kernel Mean Embeddings Patric Bonnier, Harald Oberhauser, Zoltan Szabo

ICMLW 2023 SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A Osborne

ICML 2023 Sampling-Based Nyström Approximation and Kernel Quadrature Satoshi Hayakawa, Harald Oberhauser, Terry Lyons

NeurIPS 2022 Capturing Graphs with Hypo-Elliptic Diffusions Csaba Toth, Darrick Lee, Celia Hacker, Harald Oberhauser

NeurIPS 2022 Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A Osborne

NeurIPS 2022 Positively Weighted Kernel Quadrature via Subsampling Satoshi Hayakawa, Harald Oberhauser, Terry Lyons

JMLR 2022 Signature Moments to Characterize Laws of Stochastic Processes Ilya Chevyrev, Harald Oberhauser

ICLR 2021 Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections Csaba Toth, Patric Bonnier, Harald Oberhauser

NeurIPS 2020 A Randomized Algorithm to Reduce the Support of Discrete Measures Francesco Cosentino, Harald Oberhauser, Alessandro Abate

ICML 2020 Bayesian Learning from Sequential Data Using Gaussian Processes with Signature Covariances Csaba Toth, Harald Oberhauser

JMLR 2019 Kernels for Sequentially Ordered Data Franz J. Kiraly, Harald Oberhauser