Julien Siems - RankMe

18 papers A* 5Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning State-Tracking from Code Using Linear RNNs. CoRR Julien Siems, Riccardo Grazzi, Kirill P. Kalinin, Hitesh Ballani, Babak Rahmani
2025	J	`jnl`	DeltaProduct: Increasing the Expressivity of DeltaNet Through Products of Householders. CoRR Julien Siems, Timur Carstensen, Arber Zela, Frank Hutter, Massimiliano Pontil, Riccardo Grazzi
2025	J	`jnl`	TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting. CoRR Vladyslav Moroshan, Julien Siems, Arber Zela, Timur Carstensen, Frank Hutter
2025	A*	`conf`	Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues. ICLR Riccardo Grazzi, Julien Siems, Arber Zela, Jörg K. H. Franke, Frank Hutter, Massimiliano Pontil
2024	J	`jnl`	GAMformer: In-Context Learning for Generalized Additive Models. CoRR Andreas Mueller, Julien Siems, Harsha Nori, David Salinas, Arber Zela, Rich Caruana, Frank Hutter
2024	J	`jnl`	Is Mamba Capable of In-Context Learning? CoRR Riccardo Grazzi, Julien Siems, Simon Schrodi, Thomas Brox, Frank Hutter
2024	J	`jnl`	Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models. CoRR Sathya Kamesh Bhethanabhotla, Omar Swelam, Julien Siems, David Salinas, Frank Hutter
2024	J	`jnl`	Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues. CoRR Riccardo Grazzi, Julien Siems, Jörg K. H. Franke, Arber Zela, Frank Hutter, Massimiliano Pontil
2023	A*	`conf`	Bayesian Optimization-Based Combinatorial Assignment. AAAI Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
2023	A*	`conf`	Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models. NeurIPS Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel
2023	J	`jnl`	Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models. CoRR Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel
2023	J	`jnl`	Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management. CoRR Julien Siems, Maximilian Schambach, Sebastian Schulze, Johannes S. Otterbach
2022	J	`jnl`	Bayesian Optimization-based Combinatorial Assignment. CoRR Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
2022	A*	`conf`	Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment. IJCAI Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
2021	J	`jnl`	Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment. CoRR Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken
2020	A*	`conf`	NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search. ICLR Arber Zela, Julien Siems, Frank Hutter
2020	J	`jnl`	NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search. CoRR Arber Zela, Julien Siems, Frank Hutter
2020	J	`jnl`	NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search. CoRR Julien Siems, Lucas Zimmer, Arber Zela, Jovita Lukasik, Margret Keuper, Frank Hutter