Jakob Heiss

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 13

Top Topics

Top Venues

Trans. Mach. Learn. Res.

Publications

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)
Ermis Nikiforos Soumalias, Jakob Weissteiner, Jakob Heiss, Sven Seuken
Machine Learning-Powered Combinatorial Clock Auction. AAAI (2024)
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)
Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
Bayesian Optimization-Based Combinatorial Assignment. AAAI (2023)
Ermis Soumalias, Jakob Weissteiner, Jakob Heiss, Sven Seuken
Machine Learning-powered Combinatorial Clock Auction. CoRR (2023)
William Andersson, Jakob Heiss, Florian Krach, Josef Teichmann
Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework. CoRR (2023)
Jakob Heiss, Jakob Weissteiner, Hanna S. Wutte, Sven Seuken, Josef Teichmann
NOMU: Neural Optimization-based Model Uncertainty. ICML (2022)
Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
Bayesian Optimization-based Combinatorial Assignment. CoRR (2022)
Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment. IJCAI (2022)
Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment. 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)
Jakob Heiss, Jakob Weissteiner, Hanna Wutte, Sven Seuken, Josef Teichmann
NOMU: Neural Optimization-based Model Uncertainty. CoRR (2021)
Jakob Heiss, Josef Teichmann, Hanna Wutte
How implicit regularization of Neural Networks affects the learned function - Part I. CoRR (2019)