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ORCIDCarlos G. Oliver
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2020 – today
- 2024
[c4]Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt:
Structure- and Function-Aware Substitution Matrices via Learnable Graph Matching. RECOMB 2024: 288-307- [i9]Dexiong Chen, Philip Hartout, Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt:
Endowing Protein Language Models with Structural Knowledge. CoRR abs/2401.14819 (2024) - [i8]Carlos G. Oliver, Vincent Mallet, Jérôme Waldispühl:
3D-based RNA function prediction tools in rnaglib. CoRR abs/2402.09330 (2024) - 2023
- [j5]Giovanni Visonà
, Diane Duroux, Lucas Miranda, Emese Sükei, Yiran Li, Karsten M. Borgwardt, Carlos G. Oliver:
Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information. Bioinform. 39(12) (2023) - [c3]Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt:
Unsupervised Manifold Alignment with Joint Multidimensional Scaling. ICLR 2023 - [c2]Tim Kucera, Carlos G. Oliver, Dexiong Chen, Karsten M. Borgwardt:
ProteinShake: Building datasets and benchmarks for deep learning on protein structures. NeurIPS 2023 - 2022
- [j4]Carlos G. Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton, Jérôme Waldispühl:
Vernal: a tool for mining fuzzy network motifs in RNA. Bioinform. 38(4): 970-976 (2022) - [j3]Vincent Mallet, Carlos G. Oliver, Jonathan Broadbent, William L. Hamilton, Jérôme Waldispühl:
RNAglib: a python package for RNA 2.5 D graphs. Bioinform. 38(5): 1458-1459 (2022) - [i7]Carlos G. Oliver, Dexiong Chen, Vincent Mallet, Pericles Philippopoulos, Karsten M. Borgwardt:
Approximate Network Motif Mining Via Graph Learning. CoRR abs/2206.01008 (2022) - [i6]Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt:
Unsupervised Manifold Alignment with Joint Multidimensional Scaling. CoRR abs/2207.02968 (2022) - 2021
- [i5]Vincent Mallet, Carlos G. Oliver, William L. Hamilton:
Edge-similarity-aware Graph Neural Networks. CoRR abs/2109.09432 (2021) - 2020
- [j2]Jacques Boitreaud, Vincent Mallet, Carlos G. Oliver, Jérôme Waldispühl:
OptiMol: Optimization of Binding Affinities in Chemical Space for Drug Discovery. J. Chem. Inf. Model. 60(12): 5658-5666 (2020) - [j1]Pericles Philippopoulos, Alessandro Ricottone, Carlos G. Oliver:
Difficulty Scaling in Proof of Work for Decentralized Problem Solving. Ledger 5 (2020) - [c1]Roman Sarrazin-Gendron, Hua-Ting Yao, Vladimir Reinharz, Carlos G. Oliver, Yann Ponty, Jérôme Waldispühl:
Stochastic Sampling of Structural Contexts Improves the Scalability and Accuracy of RNA 3D Module Identification. RECOMB 2020: 186-201 - [i4]Carlos G. Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton, Jérôme Waldispühl:
VeRNAl: A Tool for Mining Fuzzy Network Motifs in RNA. CoRR abs/2009.00664 (2020)
2010 – 2019
- 2019
- [i3]Vincent Mallet, Carlos G. Oliver, Nicolas Moitessier, Jérôme Waldispühl:
Leveraging binding-site structure for drug discovery with point-cloud methods. CoRR abs/1905.12033 (2019) - [i2]Pericles Philippopoulos, Alessandro Ricottone, Carlos G. Oliver:
Difficulty Scaling in Proof of Work for Decentralized Problem Solving. CoRR abs/1911.00435 (2019) - 2017
- [i1]Carlos G. Oliver, Alessandro Ricottone, Pericles Philippopoulos:
Proposal for a fully decentralized blockchain and proof-of-work algorithm for solving NP-complete problems. CoRR abs/1708.09419 (2017)
Coauthor Index
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