Philipp Hennig
73 papers · 2010–2026 · 7 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 15 separate collaboration groups - the largest holds only 47% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Philipp Hennig?
6 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Nathanael Bosch, Filip Tronarp, Nicholas Krämer
16 papers
· 2020–2024
· ICML, NeurIPS, AISTATS
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Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
ICML 2024
Parallel-in-Time Probabilistic Numerical ODE Solvers
JMLR 2024
Probabilistic ODE solvers for integration error-aware numerical optimal control
L4DC 2024
Stable Implementation of Probabilistic ODE Solvers
JMLR 2024
Bayesian numerical integration with neural networks
UAI 2023
Probabilistic Exponential Integrators
NeurIPS 2023
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
NeurIPS 2023
Fenrir: Physics-Enhanced Regression for Initial Value Problems
ICML 2022
Pick-and-Mix Information Operators for Probabilistic ODE Solvers
AISTATS 2022
Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations
AISTATS 2022
Probabilistic ODE Solutions in Millions of Dimensions
ICML 2022
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data
NeurIPS 2021
Calibrated Adaptive Probabilistic ODE Solvers
AISTATS 2021
Linear-Time Probabilistic Solution of Boundary Value Problems
NeurIPS 2021
ResNet After All: Neural ODEs and Their Numerical Solution
ICLR 2021
Differentiable Likelihoods for Fast Inversion of ’Likelihood-Free’ Dynamical Systems
ICML 2020
9 papers whose co-authors appear nowhere else under this name
Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization
AISTATS 2019
Convergence Guarantees for Adaptive Bayesian Quadrature Methods
NeurIPS 2019
Batch Bayesian Optimization via Local Penalization
AISTATS 2016
Dual Control for Approximate Bayesian Reinforcement Learning
JMLR 2016
Incremental Local Gaussian Regression
NeurIPS 2014
Fast Probabilistic Optimization from Noisy Gradients
ICML 2013
Quasi-Newton Method: A New Direction
JMLR 2013
Entropy Search for Information-Efficient Global Optimization
JMLR 2012
Optimal Reinforcement Learning for Gaussian Systems
NeurIPS 2011