Julien Siems
Cited by
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Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks
A Zela*, J Siems*, L Zimmer*, J Lukasik, M Keuper, F Hutter
International Conference on Learning Representations (ICLR), 2022
NAS-Bench-1Shot1: Benchmarking and dissecting one-shot neural architecture search
A Zela*, J Siems*, F Hutter
International Conference on Learning Representations (ICLR), 2020
Faster training of Mask R-CNN by focusing on instance boundaries
R Zimmermann*, J Siems*
Computer Vision and Image Understanding 188, 102795, 2019
Naslib: A modular and flexible neural architecture search library
M Ruchte, A Zela, JN Siems, J Grabocka, F Hutter
Bayesian Optimization-based Combinatorial Assignment
J Weissteiner*, J Heiss*, J Siems*, S Seuken
AAAI Conference on Artificial Intelligence (AAAI'23), 2023
Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment
J Weissteiner*, J Heiss*, J Siems*, S Seuken
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Is Mamba Capable of In-Context Learning?
R Grazzi*, J Siems*, S Schrodi, T Brox, F Hutter
ICLR 2024 Workshop on Mathematical and Empirical Understanding of Foundation …, 2024
Dynamic Pruning of a Neural Network via Gradient Signal-to-Noise Ratio
J Siems, A Klein, C Archambeau, M Mahsereci
8th ICML Workshop on Automated Machine Learning (AutoML), 2021
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
J Siems*, K Ditschuneit*, W Ripken*, A Lindborg*, M Schambach, ...
Advances in Neural Information Processing Systems (NeurIPS) 37, 2023
Method, device and computer program for predicting a suitable configuration of a machine learning system for a training data set
A Zela, F Hutter, J Siems, L Zimmer
US Patent App. 16/950,570, 2021
Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management
J Siems, M Schambach, S Schulze, JS Otterbach
AI for Agent Based Modeling Workshop at ICLR, 2023
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