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Harald Oberhauser
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2020 – today
- 2025
- [j7]Chad Giusti, Darrick Lee, Vidit Nanda, Harald Oberhauser:
A topological approach to mapping space signatures. Adv. Appl. Math. 163: 102787 (2025) - 2024
- [j6]Uzu Lim
, Harald Oberhauser, Vidit Nanda:
Tangent Space and Dimension Estimation with the Wasserstein Distance. SIAM J. Appl. Algebra Geom. 8(3): 650-685 (2024) - [c9]Masaki Adachi
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. AISTATS 2024: 496-504 - [i25]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 abs/2404.12219 (2024) - 2023
- [j5]Francesco Cosentino
Grid-Free Computation of Probabilistic Safety With Malliavin Calculus. IEEE Trans. Autom. Control. 68(10): 6369-6376 (2023) - [c8]Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons:
Sampling-based Nyström Approximation and Kernel Quadrature. ICML 2023: 12678-12699 - [c7]Patric Bonnier, Harald Oberhauser, Zoltán Szabó:
Kernelized Cumulants: Beyond Kernel Mean Embeddings. NeurIPS 2023 - [i24]Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons:
Sampling-based Nyström Approximation and Kernel Quadrature. CoRR abs/2301.09517 (2023) - [i23]Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne:
SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. CoRR abs/2301.11832 (2023) - [i22]Patric Bonnier, Harald Oberhauser, Zoltán Szabó:
Kernelized Cumulants: Beyond Kernel Mean Embeddings. CoRR abs/2301.12466 (2023) - [i21]Darrick Lee, Harald Oberhauser:
The Signature Kernel. CoRR abs/2305.04625 (2023) - [i20]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 abs/2306.05843 (2023) - [i19]Uzu Lim, Harald Oberhauser, Vidit Nanda:
HADES: Fast Singularity Detection with Local Measure Comparison. CoRR abs/2311.04171 (2023) - [i18]Csaba Tóth, Harald Oberhauser, Zoltán Szabó:
Random Fourier Signature Features. CoRR abs/2311.12214 (2023) - 2022
- [j4]Ilya Chevyrev, Harald Oberhauser:
Signature Moments to Characterize Laws of Stochastic Processes. J. Mach. Learn. Res. 23: 176:1-176:42 (2022) - [c6]Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne:
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. NeurIPS 2022 - [c5]Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons:
Positively Weighted Kernel Quadrature via Subsampling. NeurIPS 2022 - [c4]Csaba Tóth, Darrick Lee, Celia Hacker, Harald Oberhauser:
Capturing Graphs with Hypo-Elliptic Diffusions. NeurIPS 2022 - [i17]Csaba Tóth, Darrick Lee, Celia Hacker, Harald Oberhauser:
Capturing Graphs with Hypo-Elliptic Diffusions. CoRR abs/2205.14092 (2022) - [i16]Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne:
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. CoRR abs/2206.04734 (2022) - [i15]Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons:
Hypercontractivity Meets Random Convex Hulls: Analysis of Randomized Multivariate Cubatures. CoRR abs/2210.05787 (2022) - 2021
- [c3]Csaba Tóth, Patric Bonnier, Harald Oberhauser:
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections. ICLR 2021 - [i14]James Foster, Terry J. Lyons, Harald Oberhauser:
The shifted ODE method for underdamped Langevin MCMC. CoRR abs/2101.03446 (2021) - [i13]Harald Oberhauser, Alexander Schell:
Nonlinear Independent Component Analysis for Continuous-Time Signals. CoRR abs/2102.02876 (2021) - [i12]Patrick Kidger, James Foster, Xuechen Li, Harald Oberhauser, Terry J. Lyons:
Neural SDEs as Infinite-Dimensional GANs. CoRR abs/2102.03657 (2021) - [i11]Francesco Cosentino, Harald Oberhauser, Alessandro Abate:
Grid-Free Computation of Probabilistic Safety with Malliavin Calculus. CoRR abs/2104.14691 (2021) - [i10]Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons:
Positively Weighted Kernel Quadrature via Subsampling. CoRR abs/2107.09597 (2021) - [i9]Uzu Lim, Vidit Nanda, Harald Oberhauser:
Tangent Space and Dimension Estimation with the Wasserstein Distance. CoRR abs/2110.06357 (2021) - 2020
- [j3]Ilya Chevyrev
Persistence Paths and Signature Features in Topological Data Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 42(1): 192-202 (2020) - [j2]James Foster
An Optimal Polynomial Approximation of Brownian Motion. SIAM J. Numer. Anal. 58(3): 1393-1421 (2020) - [c2]Csaba Tóth, Harald Oberhauser:
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances. ICML 2020: 9548-9560 - [c1]Francesco Cosentino, Harald Oberhauser, Alessandro Abate:
A Randomized Algorithm to Reduce the Support of Discrete Measures. NeurIPS 2020 - [i8]Francesco Cosentino, Harald Oberhauser, Alessandro Abate:
A Randomized Algorithm to Reduce the Support of Discrete Measures. CoRR abs/2006.01757 (2020) - [i7]Francesco Cosentino, Harald Oberhauser, Alessandro Abate:
Acceleration of Descent-based Optimization Algorithms via Carathéodory's Theorem. CoRR abs/2006.01819 (2020) - [i6]Csaba Tóth, Patric Bonnier, Harald Oberhauser:
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections. CoRR abs/2006.07027 (2020)
2010 – 2019
- 2019
- [j1]Franz J. Király, Harald Oberhauser:
Kernels for Sequentially Ordered Data. J. Mach. Learn. Res. 20: 31:1-31:45 (2019) - [i5]Csaba Tóth, Harald Oberhauser:
Variational Gaussian Processes with Signature Covariances. CoRR abs/1906.08215 (2019) - 2018
- [i4]Frithjof Gressmann, Franz J. Király, Bilal A. Mateen, Harald Oberhauser:
Probabilistic supervised learning. CoRR abs/1801.00753 (2018) - [i3]Ilya Chevyrev, Vidit Nanda, Harald Oberhauser:
Persistence paths and signature features in topological data analysis. CoRR abs/1806.00381 (2018) - 2017
- [i2]Terry J. Lyons, Harald Oberhauser:
Sketching the order of events. CoRR abs/1708.09708 (2017) - 2016
- [i1]Franz J. Király, Harald Oberhauser:
Kernels for sequentially ordered data. CoRR abs/1601.08169 (2016)
Coauthor Index
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last updated on 2024-10-30 20:33 CET by the dblp team
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