Josef Teichmann

According to our database, Josef Teichmann authored at least 31 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework.

William Andersson, Jakob Heiss, Florian Krach, Josef Teichmann

Trans. Mach. Learn. Res., 2024

Learning Chaotic Systems and Long-Term Predictions with Neural Jump ODEs.

Florian Krach, Josef Teichmann

CoRR, 2024

Robust Utility Optimization via a GAN Approach.

Florian Krach, Josef Teichmann, Hanna Wutte

CoRR, 2024

Adversarial Inverse Reinforcement Learning for Market Making.

Juraj Zelman, Martin Stefanik, Moritz Weiss, Josef Teichmann

Proceedings of the 5th ACM International Conference on AI in Finance, 2024

2023

A case study for unlocking the potential of deep learning in asset-liability-management.

Thomas Krabichler, Josef Teichmann

Frontiers Artif. Intell., February, 2023

Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices.

Calypso Herrera, Florian Krach, Anastasis Kratsios, Pierre Ruyssen, Josef Teichmann

Trans. Mach. Learn. Res., 2023

Randomized Signature Methods in Optimal Portfolio Selection.

Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou

CoRR, 2023

Global universal approximation of functional input maps on weighted spaces.

Christa Cuchiero, Philipp Schmocker, Josef Teichmann

CoRR, 2023

How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function - Part II: the Multi-D Case of Two Layers with Random First Layer.

Jakob Heiss, Josef Teichmann, Hanna Wutte

CoRR, 2023

On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics.

Enea Monzio Compagnoni, Anna Scampicchio, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Discrete-Time Signatures and Randomness in Reservoir Computing.

Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann

IEEE Trans. Neural Networks Learn. Syst., 2022

Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs.

Florian Krach, Marc Nübel, Josef Teichmann

CoRR, 2022

Applications of Signature Methods to Market Anomaly Detection.

Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou

CoRR, 2022

Randomized Signature Layers for Signal Extraction in Time Series Data.

Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann

CoRR, 2022

NOMU: Neural Optimization-based Model Uncertainty.

Jakob Heiss, Jakob Weissteiner, Hanna S. Wutte, Sven Seuken, Josef Teichmann

Proceedings of the International Conference on Machine Learning, 2022

2021

Infinite wide (finite depth) Neural Networks benefit from multi-task learning unlike shallow Gaussian Processes - an exact quantitative macroscopic characterization.

Jakob Heiss, Josef Teichmann, Hanna Wutte

CoRR, 2021

Optimal Stopping via Randomized Neural Networks.

Calypso Herrera, Florian Krach, Pierre Ruyssen, Josef Teichmann

CoRR, 2021

Deep Hedging under Rough Volatility.

Blanka Horvath, Josef Teichmann, Zan Zuric

CoRR, 2021

Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering.

Calypso Herrera, Florian Krach, Josef Teichmann

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Deep Neural Networks, Generic Universal Interpolation, and Controlled ODEs.

Christa Cuchiero, Martin Larsson, Josef Teichmann

SIAM J. Math. Data Sci., 2020

Theoretical Guarantees for Learning Conditional Expectation using Controlled ODE-RNN.

Calypso Herrera, Florian Krach, Josef Teichmann

CoRR, 2020

Denise: Deep Learning based Robust PCA for Positive Semidefinite Matrices.

Calypso Herrera, Florian Krach, Josef Teichmann

CoRR, 2020

Estimating Full Lipschitz Constants of Deep Neural Networks.

Calypso Herrera, Florian Krach, Josef Teichmann

CoRR, 2020

2019

How implicit regularization of Neural Networks affects the learned function - Part I.

Jakob Heiss, Josef Teichmann, Hanna Wutte

CoRR, 2019

2017

Discrete Time Term Structure Theory and Consistent Recalibration Models.

Anja Richter, Josef Teichmann

SIAM J. Financial Math., 2017

2016

Parabolic Free Boundary Price Formation Models Under Market Size Fluctuations.

Peter A. Markowich, Josef Teichmann, Marie-Therese Wolfram

Multiscale Model. Simul., 2016

2015

A convergence result for the Emery topology and a variant of the proof of the fundamental theorem of asset pricing.

Christa Cuchiero, Josef Teichmann

Finance Stochastics, 2015

2013

Efficient Simulation and Calibration of General HJM Models by Splitting Schemes.

Philipp Dörsek, Josef Teichmann

SIAM J. Financial Math., 2013

2012

Polynomial processes and their applications to mathematical finance.

Christa Cuchiero, Martin Keller-Ressel, Josef Teichmann

Finance Stochastics, 2012

2010

Term Structure Models Driven by Wiener Processes and Poisson Measures: Existence and Positivity.

Damir Filipovic, Stefan Tappe, Josef Teichmann

SIAM J. Financial Math., 2010

2008

Absolutely Continuous Laws of Jump-Diffusions in Finite and Infinite Dimensions with Applications to Mathematical Finance.

Barbara Forster, Eva Lütkebohmert, Josef Teichmann

SIAM J. Math. Anal., 2008