Harald Oberhauser

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 39

Top Topics

Histogram Intersection

Polynomial Approximation

Bayesian Inference

Component Analysis

Top Venues

J. Mach. Learn. Res.

Publications

Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. AISTATS (2024)
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Saad Hamid, Harald Oberhauser, Michael A. Osborne
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting. CoRR (2024)
Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. CoRR (2023)
Masaki Adachi, Satoshi Hayakawa, Xingchen Wan, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. CoRR (2023)
Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons
Sampling-based Nyström Approximation and Kernel Quadrature. CoRR (2023)
Csaba Tóth, Harald Oberhauser, Zoltán Szabó
Random Fourier Signature Features. CoRR (2023)
Francesco Cosentino, Harald Oberhauser, Alessandro Abate
Grid-Free Computation of Probabilistic Safety With Malliavin Calculus. IEEE Trans. Autom. Control. 68 (10) (2023)
Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons
Sampling-based Nyström Approximation and Kernel Quadrature. ICML (2023)
Patric Bonnier, Harald Oberhauser, Zoltán Szabó
Kernelized Cumulants: Beyond Kernel Mean Embeddings. CoRR (2023)
Patric Bonnier, Harald Oberhauser, Zoltán Szabó
Kernelized Cumulants: Beyond Kernel Mean Embeddings. NeurIPS (2023)
Uzu Lim, Harald Oberhauser, Vidit Nanda
HADES: Fast Singularity Detection with Local Measure Comparison. CoRR (2023)
Darrick Lee, Harald Oberhauser
The Signature Kernel. CoRR (2023)
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. CoRR (2022)
Ilya Chevyrev, Harald Oberhauser
Signature Moments to Characterize Laws of Stochastic Processes. J. Mach. Learn. Res. 23 (2022)
Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons
Positively Weighted Kernel Quadrature via Subsampling. NeurIPS (2022)
Csaba Tóth, Darrick Lee, Celia Hacker, Harald Oberhauser
Capturing Graphs with Hypo-Elliptic Diffusions. NeurIPS (2022)
Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons
Hypercontractivity Meets Random Convex Hulls: Analysis of Randomized Multivariate Cubatures. CoRR (2022)
Csaba Tóth, Darrick Lee, Celia Hacker, Harald Oberhauser
Capturing Graphs with Hypo-Elliptic Diffusions. CoRR (2022)
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. NeurIPS (2022)
Patrick Kidger, James Foster, Xuechen Li, Harald Oberhauser, Terry J. Lyons
Neural SDEs as Infinite-Dimensional GANs. CoRR (2021)
James Foster, Terry J. Lyons, Harald Oberhauser
The shifted ODE method for underdamped Langevin MCMC. CoRR (2021)
Csaba Tóth, Patric Bonnier, Harald Oberhauser
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections. ICLR (2021)
Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons
Positively Weighted Kernel Quadrature via Subsampling. CoRR (2021)
Francesco Cosentino, Harald Oberhauser, Alessandro Abate
Grid-Free Computation of Probabilistic Safety with Malliavin Calculus. CoRR (2021)
Uzu Lim, Vidit Nanda, Harald Oberhauser
Tangent Space and Dimension Estimation with the Wasserstein Distance. CoRR (2021)
Harald Oberhauser, Alexander Schell
Nonlinear Independent Component Analysis for Continuous-Time Signals. CoRR (2021)
James Foster, Terry J. Lyons, Harald Oberhauser
An Optimal Polynomial Approximation of Brownian Motion. SIAM J. Numer. Anal. 58 (3) (2020)
Francesco Cosentino, Harald Oberhauser, Alessandro Abate
A Randomized Algorithm to Reduce the Support of Discrete Measures. NeurIPS (2020)
Francesco Cosentino, Harald Oberhauser, Alessandro Abate
A Randomized Algorithm to Reduce the Support of Discrete Measures. CoRR (2020)
Francesco Cosentino, Harald Oberhauser, Alessandro Abate
Acceleration of Descent-based Optimization Algorithms via Carathéodory's Theorem. CoRR (2020)
Ilya Chevyrev, Vidit Nanda, Harald Oberhauser
Persistence Paths and Signature Features in Topological Data Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 42 (1) (2020)
Csaba Tóth, Harald Oberhauser
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances. ICML (2020)
Csaba Tóth, Patric Bonnier, Harald Oberhauser
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections. CoRR (2020)
Franz J. Király, Harald Oberhauser
Kernels for Sequentially Ordered Data. J. Mach. Learn. Res. 20 (2019)
Csaba Tóth, Harald Oberhauser
Variational Gaussian Processes with Signature Covariances. CoRR (2019)
Frithjof Gressmann, Franz J. Király, Bilal A. Mateen, Harald Oberhauser
Probabilistic supervised learning. CoRR (2018)
Ilya Chevyrev, Vidit Nanda, Harald Oberhauser
Persistence paths and signature features in topological data analysis. CoRR (2018)
Terry J. Lyons, Harald Oberhauser
Sketching the order of events. CoRR (2017)
Franz J. Király, Harald Oberhauser
Kernels for sequentially ordered data. CoRR (2016)