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ORCIDLadislav Rampásek
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2020 – today
- 2024
[j6]Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampásek:
Attending to Graph Transformers. Trans. Mach. Learn. Res. 2024 (2024)- [c5]Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek:
Graph Positional and Structural Encoder. ICML 2024 - [i11]Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot
, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio:
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024) - 2023
- [j5]Dominic Masters, Josef Dean, Kerstin Kläser, Zhiyi Li, Samuel Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W. Fitzgibbon, Shenyang Huang, Ladislav Rampásek, Dominique Beaini:
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. Trans. Mach. Learn. Res. 2023 (2023) - [i10]Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W. Fitzgibbon, Shenyang Huang, Ladislav Rampásek, Dominique Beaini:
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. CoRR abs/2302.02947 (2023) - [i9]Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampásek:
Attending to Graph Transformers. CoRR abs/2302.04181 (2023) - [i8]Renming Liu, Semih Cantürk, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek:
Graph Positional and Structural Encoder. CoRR abs/2307.07107 (2023) - 2022
- [c4]Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek:
Taxonomy of Benchmarks in Graph Representation Learning. LoG 2022: 6 - [c3]Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini:
Long Range Graph Benchmark. NeurIPS 2022 - [c2]Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini:
Recipe for a General, Powerful, Scalable Graph Transformer. NeurIPS 2022 - [i7]Ladislav Rampásek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini:
Recipe for a General, Powerful, Scalable Graph Transformer. CoRR abs/2205.12454 (2022) - [i6]Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek:
Taxonomy of Benchmarks in Graph Representation Learning. CoRR abs/2206.07729 (2022) - [i5]Vijay Prakash Dwivedi, Ladislav Rampásek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini:
Long Range Graph Benchmark. CoRR abs/2206.08164 (2022) - [i4]Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Ladislav Rampásek, Dominique Beaini:
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction. CoRR abs/2212.02229 (2022) - 2021
- [c1]Ladislav Rampásek, Guy Wolf:
Hierarchical Graph Neural Nets can Capture Long-Range Interactions. MLSP 2021: 1-6 - [i3]Ladislav Rampásek, Guy Wolf:
Hierarchical graph neural nets can capture long-range interactions. CoRR abs/2107.07432 (2021) - [i2]Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek:
Towards a Taxonomy of Graph Learning Datasets. CoRR abs/2110.14809 (2021) - 2020
- [b1]Ladislav Rampásek:
Latent-variable models for drug response prediction and genetic testing. University of Toronto, Canada, 2020
2010 – 2019
- 2019
- [j4]Ladislav Rampásek, Daniel Hidru, Petr Smirnov, Benjamin Haibe-Kains, Anna Goldenberg:
Dr.VAE: improving drug response prediction via modeling of drug perturbation effects. Bioinform. 35(19): 3743-3751 (2019) - 2017
- [i1]Chun-Hao Chang, Ladislav Rampásek, Anna Goldenberg:
Dropout Feature Ranking for Deep Learning Models. CoRR abs/1712.08645 (2017) - 2016
- [j3]Aryan Arbabi, Ladislav Rampásek, Michael Brudno:
Cell-free DNA fragment-size distribution analysis for non-invasive prenatal CNV prediction. Bioinform. 32(11): 1662-1669 (2016) - [j2]Ladislav Rampásek, Randi M. Jimenez, Andrej Lupták, Tomás Vinar, Brona Brejová:
RNA motif search with data-driven element ordering. BMC Bioinform. 17: 216 (2016) - 2014
- [j1]Ladislav Rampásek, Aryan Arbabi, Michael Brudno:
Probabilistic method for detecting copy number variation in a fetal genome using maternal plasma sequencing. Bioinform. 30(12): 212-218 (2014)
Coauthor Index
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