Get started
Author

Jakob Heiss

Observed names: Heiss, Jakob, Heiss, Jakob Michael
ORCID: 0000-0003-1447-6782
Observed ORCID: 0000-0003-1447-6782
OpenAlex ID: A5010858034
How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer
2019 · Heiss, Jakob, Teichmann, Josef, et al. · arXiv (Cornell University) · 21
PDF
NOMU: Neural Optimization-based Model Uncertainty
2021 · Heiss, Jakob, Weissteiner, Jakob, et al. · Zurich Open Repository and Archive (University of Zurich) · 18
PDF
Bayesian Optimization-Based Combinatorial Assignment
2023 · Jakob Weissteiner, Jakob Heiss, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 16
PDF
Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment
2022 · Jakob Weissteiner, Jakob Heiss, et al. · International Joint Conference on Artificial Intelligence · 13
PDF
How Infinitely Wide Neural Networks Can Benefit from Multi-task Learning - an Exact Macroscopic Characterization
2021 · Heiss, Jakob, Teichmann, Josef, et al. · arXiv (Cornell University) · 9
PDF
CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk
2025 · Azizi, Ilia, Bodik, Juraj, et al. · arXiv (Cornell University) · 8
PDF
How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part II: the Multi-D Case of Two Layers with Random First Layer
2023 · Heiss, Jakob, Teichmann, Josef, et al. · arXiv (Cornell University) · 8
PDF
Nonparametric filtering, estimation and classification using neural jump ODEs
2025 · Jakob Heiss, Florian Krach, et al. · Statistics & Risk Modeling · 6
PDF
Machine Learning-Powered Combinatorial Clock Auction
2024 · Ermis Nikiforos Soumalias, Jakob Weissteiner, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 5
PDF
JUCAL: Jointly Calibrating Aleatoric and Epistemic Uncertainty in Classification Tasks
2026 · Heiss, Jakob, Lambrecht, Sören, et al. · arXiv (Cornell University) · 3
PDF
Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All
2024 · Soumalias, Ermis, Heiss, Jakob, et al. · arXiv (Cornell University) · 2
PDF
Revealing the temporal dynamics of antibiotic anomalies in the infant gut microbiome with neural jump ODEs
2025 · Adamov, Anja, Chardonnet, Markus, et al. · arXiv (Cornell University) · 1
PDF
Revealing the temporal dynamics of antibiotic anomalies in the infant gut microbiome with neural jump ODEs
2026 · Adamov, Anja, Chardonnet, Markus, et al. · Zenodo (CERN European Organization for Nuclear Research)
Revealing the temporal dynamics of antibiotic anomalies in the infant gut microbiome with neural jump ODEs
2026 · Adamov, Anja, Chardonnet, Markus, et al. · Zenodo (CERN European Organization for Nuclear Research)
Implicit Regularization of Large Neural Networks via Mean-Field Formulation
2026 · Acciaio, Beatrice, Heiss, Jakob, et al. · arXiv (Cornell University)
PDF
Infinite width (finite depth) neural networks benefit from multi-task learning unlike shallow Gaussian Processes - an exact quantitative macroscopic characterization
2021 · Heiss, Jakob, Teichmann, Josef, et al. · Repository for Publications and Research Data (ETH Zurich)
Works count: 22
Citation count: 115
H-index: 7
I10-index: 4
Year
Topic
Type