Karolis Martinkus

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 20

Top Topics

Graph Representation

Diffusion Models

Top Venues

Publications

Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer
GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks. ICLR (2024)
Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer
Efficient and Scalable Graph Generation through Iterative Local Expansion. ICLR (2024)
Karolis Martinkus, Jan Ludwiczak, Kyunghyun Cho, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hötzel, Arvind Rajpal, Yan Wu, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas
AbDiffuser: Full-Atom Generation of In-Vitro Functioning Antibodies. CoRR (2023)
Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer
Agent-based Graph Neural Networks. ICLR (2023)
Karolis Martinkus, Jan Ludwiczak, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hötzel, Arvind Rajpal, Yan Wu, Kyunghyun Cho, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas
AbDiffuser: full-atom generation of in-vitro functioning antibodies. NeurIPS (2023)
Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer
Efficient and Scalable Graph Generation through Iterative Local Expansion. CoRR (2023)
Mihai Babiac, Karolis Martinkus, Roger Wattenhofer
Discovering Graph Generation Algorithms. CoRR (2023)
Jeremia Geiger, Karolis Martinkus, Oliver Richter, Roger Wattenhofer
Automating Rigid Origami Design. IJCAI (2023)
Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer
SPECTRE : Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators. CoRR (2022)
Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators. ICML (2022)
Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer
Agent-based Graph Neural Networks. CoRR (2022)
Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer
DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees. CoRR (2022)
Jeremia Geiger, Karolis Martinkus, Oliver Richter, Roger Wattenhofer
Automating Rigid Origami Design. CoRR (2022)
Kilian Konstantin Haefeli, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer
Diffusion Models for Graphs Benefit From Discrete State Spaces. CoRR (2022)
Yue Ding, Karolis Martinkus, Damian Pascual, Simon Clematide, Roger Wattenhofer
On Isotropy Calibration of Transformer Models. Insights@ACL (2022)
Yue Ding, Karolis Martinkus, Damian Pascual, Simon Clematide, Roger Wattenhofer
On Isotropy Calibration of Transformers. CoRR (2021)
Pál András Papp, Karolis Martinkus, Lukas Faber, Roger Wattenhofer
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks. NeurIPS (2021)
Karolis Martinkus, Aurélien Lucchi, Nathanaël Perraudin
Scalable Graph Networks for Particle Simulations. AAAI (2021)
Pál András Papp, Karolis Martinkus, Lukas Faber, Roger Wattenhofer
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks. CoRR (2021)
Karolis Martinkus, Aurélien Lucchi, Nathanaël Perraudin
Scalable Graph Networks for Particle Simulations. CoRR (2020)