Adam Arany

According to our database, Adam Arany authored at least 26 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Smoothing unadjusted Langevin algorithms for nonsmooth composite potential functions.

Susan Ghaderi, Masoud Ahookhosh, Adam Arany, Alexander Skupin, Panagiotis Patrinos, Yves Moreau

Appl. Math. Comput., March, 2024

MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information.

Wouter Heyndrickx, Lewis H. Mervin, Tobias Morawietz, Noé Sturm, Lukas Friedrich, Adam Zalewski, Anastasia Pentina, Lina Humbeck, Martijn Oldenhof, Ritsuya Niwayama, Peter Schmidtke, Nikolas Fechner, Jaak Simm, Adam Arany, Nicolas Drizard, Rama Jabal, Arina Afanasyeva, Regis Loeb, Shlok Verma, Simon Harnqvist, Matthew Holmes, Balazs Pejo, Maria Telenczuk, Nicholas Holway, Arne Dieckmann, Nicola Rieke, Friederike Zumsande, Djork-Arné Clevert, Michael Krug, Christopher N. Luscombe, Darren V. S. Green, Peter Ertl, Peter Antal, David Marcus, Nicolas Do Huu, Hideyoshi Fuji, Stephen D. Pickett, Gergely Ács, Eric Boniface, Bernd Beck, Yax Sun, Arnaud Gohier, Friedrich Rippmann, Ola Engkvist, Andreas H. Göller, Yves Moreau, Mathieu N. Galtier, Ansgar Schuffenhauer, Hugo Ceulemans

J. Chem. Inf. Model., 2024

Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression Labels.

Emma Svensson, Hannah Rosa Friesacher, Susanne Winiwarter, Lewis H. Mervin, Adam Arany, Ola Engkvist

CoRR, 2024

Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models.

Hannah Rosa Friesacher, Ola Engkvist, Lewis H. Mervin, Yves Moreau, Adam Arany

CoRR, 2024

Temporal Evaluation of Uncertainty Quantification Under Distribution Shift.

Emma Svensson, Hannah Rosa Friesacher, Adam Arany, Lewis H. Mervin, Ola Engkvist

Proceedings of the AI in Drug Discovery - First International Workshop, 2024

Temporal Evaluation of Probability Calibration with Experimental Errors.

Hannah Rosa Friesacher, Emma Svensson, Adam Arany, Lewis H. Mervin, Ola Engkvist

Proceedings of the AI in Drug Discovery - First International Workshop, 2024

Model Based Clustering of Time Series Utilizing Expert ODEs.

András Formanek, Edward De Brouwer, Péter Antal, Yves Moreau, Adam Arany

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

Atom-Level Optical Chemical Structure Recognition with Limited Supervision.

Martijn Oldenhof, Edward De Brouwer, Adam Arany, Yves Moreau

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection.

Martijn Oldenhof, Adam Arany, Yves Moreau, Edward De Brouwer

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Industry-Scale Orchestrated Federated Learning for Drug Discovery.

Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Wouter Heyndrickx, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Antoine Simon, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Collaborative Drug Discovery: Inference-level Data Protection Perspective.

Balazs Pejo, Mina Remeli, Adam Arany, Mathieu Galtier, Gergely Ács

Trans. Data Priv., 2022

Industry-Scale Orchestrated Federated Learning for Drug Discovery.

Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier

CoRR, 2022

SparseChem: Fast and accurate machine learning model for small molecules.

Adam Arany, Jaak Simm, Martijn Oldenhof, Yves Moreau

CoRR, 2022

2021

A novel method for data fusion over entity-relation graphs and its application to protein-protein interaction prediction.

Daniele Raimondi, Jaak Simm, Adam Arany, Yves Moreau

Bioinform., 2021

Expressive Graph Informer Networks.

Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Latent Convergent Cross Mapping.

Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau

Proceedings of the 9th International Conference on Learning Representations, 2021

Self-labeling of Fully Mediating Representations by Graph Alignment.

Martijn Oldenhof, Adam Arany, Yves Moreau, Jaak Simm

Proceedings of the Artificial Intelligence and Machine Learning, 2021

2020

ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning.

Martijn Oldenhof, Adam Arany, Yves Moreau, Jaak Simm

J. Chem. Inf. Model., 2020

Multilevel Gibbs Sampling for Bayesian Regression.

Joris Tavernier, Jaak Simm, Adam Arany, Karl Meerbergen, Yves Moreau

CoRR, 2020

2019

Graph Informer Networks for Molecules.

Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau

CoRR, 2019

GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series.

Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

SMURFF: A High-Performance Framework for Matrix Factorization Methods.

Tom Vander Aa, Imen Chakroun, Tom Ashby, Jaak Simm, Adam Arany, Yves Moreau, Thanh Le Van, José Felipe Golib Dzib, Jörg K. Wegner, Vladimir I. Chupakhin, Hugo Ceulemans, Roel Wuyts, Wilfried Verachtert

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification.

Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau

CoRR, 2018

Gene prioritization using Bayesian matrix factorization with genomic and phenotypic side information.

Pooya Zakeri, Jaak Simm, Adam Arany, Sarah ElShal, Yves Moreau

Bioinform., 2018

2017

Macau: Scalable Bayesian factorization with high-dimensional side information using MCMC.

Jaak Simm, Adam Arany, Pooya Zakeri, Tom Haber, Jörg K. Wegner, Vladimir I. Chupakhin, Hugo Ceulemans, Yves Moreau

Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

2016

A Comprehensive Comparison of Two MEDLINE Annotators for Disease and Gene Linkage: Sometimes Less is More.

Sarah ElShal, Jaak Simm, Adam Arany, Pooya Zakeri, Jesse Davis, Yves Moreau

Proceedings of the Bioinformatics and Biomedical Engineering, 2016