Josef Teichmann

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 29

Top Topics

Utility Elicitation

Gaussian Processes

Robust Principal Component Analysis

Top Venues

Trans. Mach. Learn. Res.

Finance Stochastics

SIAM J. Math. Data Sci.

Publications

Florian Krach, Josef Teichmann
Learning Chaotic Systems and Long-Term Predictions with Neural Jump ODEs. CoRR (2024)
William Andersson, Jakob Heiss, Florian Krach, Josef Teichmann
Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework. Trans. Mach. Learn. Res. 2024 (2024)
Florian Krach, Josef Teichmann, Hanna Wutte
Robust Utility Optimization via a GAN Approach. CoRR (2024)
Enea Monzio Compagnoni, Anna Scampicchio, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann
On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics. IJCNN (2023)
Jakob Heiss, Josef Teichmann, Hanna Wutte
How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function - Part II: the Multi-D Case of Two Layers with Random First Layer. CoRR (2023)
Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou
Randomized Signature Methods in Optimal Portfolio Selection. CoRR (2023)
Calypso Herrera, Florian Krach, Anastasis Kratsios, Pierre Ruyssen, Josef Teichmann
Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices. Trans. Mach. Learn. Res. 2023 (2023)
Christa Cuchiero, Philipp Schmocker, Josef Teichmann
Global universal approximation of functional input maps on weighted spaces. CoRR (2023)
Thomas Krabichler, Josef Teichmann
A case study for unlocking the potential of deep learning in asset-liability-management. Frontiers Artif. Intell. 6 (2023)
William Andersson, Jakob Heiss, Florian Krach, Josef Teichmann
Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework. CoRR (2023)
Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann
Discrete-Time Signatures and Randomness in Reservoir Computing. IEEE Trans. Neural Networks Learn. Syst. 33 (11) (2022)
Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou
Applications of Signature Methods to Market Anomaly Detection. CoRR (2022)
Jakob Heiss, Jakob Weissteiner, Hanna S. Wutte, Sven Seuken, Josef Teichmann
NOMU: Neural Optimization-based Model Uncertainty. ICML (2022)
Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann
Randomized Signature Layers for Signal Extraction in Time Series Data. CoRR (2022)
Florian Krach, Marc Nübel, Josef Teichmann
Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs. CoRR (2022)
Calypso Herrera, Florian Krach, Pierre Ruyssen, Josef Teichmann
Optimal Stopping via Randomized Neural Networks. CoRR (2021)
Jakob Heiss, Josef Teichmann, Hanna Wutte
Infinite wide (finite depth) Neural Networks benefit from multi-task learning unlike shallow Gaussian Processes - an exact quantitative macroscopic characterization. CoRR (2021)
Calypso Herrera, Florian Krach, Josef Teichmann
Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering. ICLR (2021)
Jakob Heiss, Jakob Weissteiner, Hanna Wutte, Sven Seuken, Josef Teichmann
NOMU: Neural Optimization-based Model Uncertainty. CoRR (2021)
Blanka Horvath, Josef Teichmann, Zan Zuric
Deep Hedging under Rough Volatility. CoRR (2021)
Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann
Discrete-time signatures and randomness in reservoir computing. CoRR (2020)
Calypso Herrera, Florian Krach, Josef Teichmann
Estimating Full Lipschitz Constants of Deep Neural Networks. CoRR (2020)
Calypso Herrera, Florian Krach, Josef Teichmann
Denise: Deep Learning based Robust PCA for Positive Semidefinite Matrices. CoRR (2020)
Christa Cuchiero, Martin Larsson, Josef Teichmann
Deep Neural Networks, Generic Universal Interpolation, and Controlled ODEs. SIAM J. Math. Data Sci. 2 (3) (2020)
Calypso Herrera, Florian Krach, Josef Teichmann
Theoretical Guarantees for Learning Conditional Expectation using Controlled ODE-RNN. CoRR (2020)
Jakob Heiss, Josef Teichmann, Hanna Wutte
How implicit regularization of Neural Networks affects the learned function - Part I. CoRR (2019)
Anja Richter, Josef Teichmann
Discrete Time Term Structure Theory and Consistent Recalibration Models. SIAM J. Financial Math. 8 (1) (2017)
Peter A. Markowich, Josef Teichmann, Marie-Therese Wolfram
Parabolic Free Boundary Price Formation Models Under Market Size Fluctuations. Multiscale Model. Simul. 14 (4) (2016)
Christa Cuchiero, Josef Teichmann
A convergence result for the Emery topology and a variant of the proof of the fundamental theorem of asset pricing. Finance Stochastics 19 (4) (2015)
Philipp Dörsek, Josef Teichmann
Efficient Simulation and Calibration of General HJM Models by Splitting Schemes. SIAM J. Financial Math. 4 (1) (2013)
Christa Cuchiero, Martin Keller-Ressel, Josef Teichmann
Polynomial processes and their applications to mathematical finance. Finance Stochastics 16 (4) (2012)
Damir Filipovic, Stefan Tappe, Josef Teichmann
Term Structure Models Driven by Wiener Processes and Poisson Measures: Existence and Positivity. SIAM J. Financial Math. 1 (1) (2010)
Barbara Forster, Eva Lütkebohmert, Josef Teichmann
Absolutely Continuous Laws of Jump-Diffusions in Finite and Infinite Dimensions with Applications to Mathematical Finance. SIAM J. Math. Anal. 40 (5) (2008)