Julian Stier - RankMe

21 papers B 5Journal 11Unranked 4

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Efficient NAS with FaDE on Hierarchical Spaces. IDA (2) Simon Neumeyer, Julian Stier, Michael Granitzer
2024	J	`jnl`	Efficient NAS with FaDE on Hierarchical Spaces. CoRR Simon Neumeyer, Julian Stier, Michael Granitzer
2024	—	`conf`	MCGRAN: Multi-conditional Graph Generation for Neural Architecture Search. LOD (1) Sathish Purushothaman, Julian Stier, Michael Granitzer
2024	J	`jnl`	Structure of Artificial Neural Networks - Empirical Investigations. CoRR Julian Stier
2024	—	`—`	Structure of Artificial Neural Networks: Empirical Investigations. Julian Stier
2023	—	`conf`	GRAN Is Superior to GraphRNN: Node Orderings, Kernel- and Graph Embeddings-Based Metrics for Graph Generators. LOD (1) Ousmane Touat, Julian Stier, Pierre-Edouard Portier, Michael Granitzer
2023	J	`jnl`	GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators. CoRR Ousmane Touat, Julian Stier, Pierre-Edouard Portier, Michael Granitzer
2022	J	`jnl`	deepstruct - linking deep learning and graph theory. Softw. Impacts Julian Stier, Michael Granitzer
2021	B	`conf`	Correlation Analysis between the Robustness of Sparse Neural Networks and their Random Hidden Structural Priors. KES Mehdi Ben Amor, Julian Stier, Michael Granitzer
2021	J	`jnl`	Correlation Analysis between the Robustness of Sparse Neural Networks and their Random Hidden Structural Priors. CoRR Mehdi Ben Amor, Julian Stier, Michael Granitzer
2021	B	`conf`	DeepGG: A Deep Graph Generator. IDA Julian Stier, Michael Granitzer
2021	B	`conf`	Evofficient: Reproducing a Cartesian Genetic Programming Method. EuroGP Lorenz Wendlinger, Julian Stier, Michael Granitzer
2021	—	`conf`	Experiments on Properties of Hidden Structures of Sparse Neural Networks. LOD Julian Stier, Harshil Darji, Michael Granitzer
2021	J	`jnl`	Experiments on Properties of Hidden Structures of Sparse Neural Networks. CoRR Julian Stier, Harshil Darji, Michael Granitzer
2021	J	`jnl`	Spatio-Temporal Machine Learning Analysis of Social Media Data and Refugee Movement Statistics. ISPRS Int. J. Geo Inf. Clemens Havas, Lorenz Wendlinger, Julian Stier, Sahib Julka, Veronika Krieger, Cornelia Ferner, Andreas Petutschnig, Michael Granitzer, Stefan Wegenkittl, Bernd Resch
2021	J	`jnl`	deepstruct - linking deep learning and graph theory. CoRR Julian Stier, Michael Granitzer
2020	J	`jnl`	Deep Graph Generators. CoRR Julian Stier, Michael Granitzer
2019	J	`jnl`	Analysing Neural Network Topologies: a Game Theoretic Approach. CoRR Julian Stier, Gabriele Gianini, Michael Granitzer, Konstantin Ziegler
2019	B	`conf`	Structural Analysis of Sparse Neural Networks. KES Julian Stier, Michael Granitzer
2019	J	`jnl`	Structural Analysis of Sparse Neural Networks. CoRR Julian Stier, Michael Granitzer
2018	B	`conf`	Analysing Neural Network Topologies: a Game Theoretic Approach. KES Julian Stier, Gabriele Gianini, Michael Granitzer, Konstantin Ziegler