148 entries « ‹ 1 of 3
› » 2025
Shternshis, Andrey; Tong, Bangzhuo; Skalkidou, Alkistis; Wählby, Carolina; Zachariah, Dave; Hugerth, Luisa W; Singh, Prashant
Predicting allergy and postpartum depression from an incomplete compositional microbiome Journal Article
In: bioRxiv, pp. 2025–02, 2025.
@article{shternshis2025predicting,
title = {Predicting allergy and postpartum depression from an incomplete compositional microbiome},
author = {Andrey Shternshis and Bangzhuo Tong and Alkistis Skalkidou and Carolina Wählby and Dave Zachariah and Luisa W Hugerth and Prashant Singh},
year = {2025},
date = {2025-01-01},
journal = {bioRxiv},
pages = {2025–02},
publisher = {Cold Spring Harbor Laboratory},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nautiyal, Mayank; Gheorghe, Stela Arranz; Stefa, Kristiana; Ju, Li; Sintorn, Ida-Maria; Singh, Prashant
PARIC: Probabilistic Attention Regularization for Language Guided Image Classification from Pre-trained Vison Language Models Journal Article
In: arXiv preprint arXiv:2503.11360, 2025.
@article{nautiyal2025paric,
title = {PARIC: Probabilistic Attention Regularization for Language Guided Image Classification from Pre-trained Vison Language Models},
author = {Mayank Nautiyal and Stela Arranz Gheorghe and Kristiana Stefa and Li Ju and Ida-Maria Sintorn and Prashant Singh},
year = {2025},
date = {2025-01-01},
journal = {arXiv preprint arXiv:2503.11360},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Azimi-Mousolou, Vahid; Singh, Prashant
Variational M-Partite Geometric Entanglement Algorithm Journal Article
In: arXiv preprint arXiv:2503.20056, 2025.
@article{azimi2025variational,
title = {Variational M-Partite Geometric Entanglement Algorithm},
author = {Vahid Azimi-Mousolou and Prashant Singh},
year = {2025},
date = {2025-01-01},
journal = {arXiv preprint arXiv:2503.20056},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Zhang, Tianru; Ju, Li; Singh, Prashant; Toor, Salman
InfoHier: Hierarchical Information Extraction via Encoding and Embedding Journal Article
In: arXiv preprint arXiv:2501.08717, 2025.
@article{zhang2025texttt,
title = {InfoHier: Hierarchical Information Extraction via Encoding and Embedding},
author = {Tianru Zhang and Li Ju and Prashant Singh and Salman Toor},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
journal = {arXiv preprint arXiv:2501.08717},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Karakulev, Aleksandr; Zafar, Usama; Toor, Salman; Singh, Prashant
Bayesian Robust Aggregation for Federated Learning Journal Article
In: arXiv preprint arXiv:2505.02490, 2025.
@article{karakulev2025bayesian,
title = {Bayesian Robust Aggregation for Federated Learning},
author = {Aleksandr Karakulev and Usama Zafar and Salman Toor and Prashant Singh},
year = {2025},
date = {2025-01-01},
journal = {arXiv preprint arXiv:2505.02490},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nautiyal, Mayank; Hellander, Andreas; Singh, Prashant
ConDiSim: Conditional Diffusion Models for Simulation Based Inference Journal Article
In: arXiv preprint arXiv:2505.08403, 2025.
@article{nautiyal2025condisim,
title = {ConDiSim: Conditional Diffusion Models for Simulation Based Inference},
author = {Mayank Nautiyal and Andreas Hellander and Prashant Singh},
year = {2025},
date = {2025-01-01},
journal = {arXiv preprint arXiv:2505.08403},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ju, Li; Andersson, Max; Fredriksson, Stina; Glöckner, Edward; Hellander, Andreas; Vats, Ekta; Singh, Prashant
Exploiting the Asymmetric Uncertainty Structure of Pre-trained VLMs on the Unit Hypersphere Conference
Advances in Neural Information Processing Systems (NeurIPS), 2025.
@conference{ju2025exploiting,
title = {Exploiting the Asymmetric Uncertainty Structure of Pre-trained VLMs on the Unit Hypersphere},
author = {Li Ju and Max Andersson and Stina Fredriksson and Edward Glöckner and Andreas Hellander and Ekta Vats and Prashant Singh},
url = {https://neurips.cc/virtual/2025/poster/116582
https://arxiv.org/abs/2505.11029},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
journal = {arXiv preprint arXiv:2505.11029},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Zafar, Usama; Teixeira, André; Toor, Salman
Robust federated learning against poisoning attacks: a gan-based defense framework Journal Article
In: arXiv preprint arXiv:2503.20884, 2025.
@article{zafar2025robust,
title = {Robust federated learning against poisoning attacks: a gan-based defense framework},
author = {Usama Zafar and André Teixeira and Salman Toor},
year = {2025},
date = {2025-01-01},
journal = {arXiv preprint arXiv:2503.20884},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2024
Fronk, Colby; Yun, Jaewoong; Singh, Prashant; Petzold, Linda
Bayesian polynomial neural networks and polynomial neural ordinary differential equations Journal Article
In: PLOS Computational Biology, 2024.
@article{fronk2023bayesian,
title = {Bayesian polynomial neural networks and polynomial neural ordinary differential equations},
author = {Colby Fronk and Jaewoong Yun and Prashant Singh and Linda Petzold},
year = {2024},
date = {2024-09-01},
urldate = {2023-01-01},
journal = {PLOS Computational Biology},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Karakulev, Aleksandr; Zachariah, Dave; Singh, Prashant
Adaptive Parameter-Free Robust Learning using Latent Bernoulli Variables Conference
Proceedings of the 41st International Conference on Machine Learning, 2024.
@conference{karakulev2023adaptive,
title = {Adaptive Parameter-Free Robust Learning using Latent Bernoulli Variables},
author = {Aleksandr Karakulev and Dave Zachariah and Prashant Singh},
url = {https://icml.cc/virtual/2024/poster/32797},
year = {2024},
date = {2024-07-25},
urldate = {2023-01-01},
booktitle = {Proceedings of the 41st International Conference on Machine Learning},
journal = {arXiv preprint arXiv:2312.00585},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Ju, Li; Zhang, Tianru; Toor, Salman; Hellander, Andreas
Accelerating Fair Federated Learning: Adaptive Federated Adam Journal Article
In: IEEE Transactions on Machine Learning in Communications and Networking, vol. 2, pp. 1017 - 1032, 2024.
@article{DBLP:journals/corr/abs-2301-09357,
title = {Accelerating Fair Federated Learning: Adaptive Federated Adam},
author = {Li Ju and Tianru Zhang and Salman Toor and Andreas Hellander},
url = {https://ieeexplore.ieee.org/abstract/document/10584508},
doi = {10.1109/TMLCN.2024.3423648},
year = {2024},
date = {2024-07-04},
urldate = {2023-01-01},
journal = {IEEE Transactions on Machine Learning in Communications and Networking},
volume = {2},
pages = {1017 - 1032},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ju, Li; Hellander, Andreas; Spjuth, Ola
Federated learning for predicting compound mechanism of action based on image-data from cell painting Journal Article
In: Artificial Intelligence in the Life Sciences, vol. 5, pp. 100098, 2024.
@article{ju2024federated,
title = {Federated learning for predicting compound mechanism of action based on image-data from cell painting},
author = {Li Ju and Andreas Hellander and Ola Spjuth},
url = {https://www.sciencedirect.com/science/article/pii/S2667318524000059},
doi = {10.1016/j.ailsci.2024.100098},
year = {2024},
date = {2024-06-01},
journal = {Artificial Intelligence in the Life Sciences},
volume = {5},
pages = {100098},
abstract = {Having access to sufficient data is essential in order to train accurate machine learning models, but much data is not publicly available. In drug discovery this is particularly evident, as much data is withheld at pharmaceutical companies for various reasons. Federated Learning (FL) aims at training a joint model between multiple parties but without disclosing data between the parties. In this work, we leverage Federated Learning to predict compound Mechanism of Action (MoA) using fluorescence image data from cell painting. Our study evaluates the effectiveness and efficiency of FL, comparing to non-collaborative and data-sharing collaborative learning in diverse scenarios. Specifically, we investigate the impact of data heterogeneity across participants on MoA prediction, an essential concern in real-life applications of FL, and demonstrate the benefits for all involved parties. This work highlights the potential of federated learning in multi-institutional collaborative machine learning for drug discovery and assessment of chemicals, offering a promising avenue to overcome data-sharing constraints.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Having access to sufficient data is essential in order to train accurate machine learning models, but much data is not publicly available. In drug discovery this is particularly evident, as much data is withheld at pharmaceutical companies for various reasons. Federated Learning (FL) aims at training a joint model between multiple parties but without disclosing data between the parties. In this work, we leverage Federated Learning to predict compound Mechanism of Action (MoA) using fluorescence image data from cell painting. Our study evaluates the effectiveness and efficiency of FL, comparing to non-collaborative and data-sharing collaborative learning in diverse scenarios. Specifically, we investigate the impact of data heterogeneity across participants on MoA prediction, an essential concern in real-life applications of FL, and demonstrate the benefits for all involved parties. This work highlights the potential of federated learning in multi-institutional collaborative machine learning for drug discovery and assessment of chemicals, offering a promising avenue to overcome data-sharing constraints.
Cheng, Liang; Singh, Prashant; Ferranti, Francesco
Transfer learning-assisted inverse modeling in nanophotonics based on mixture density networks Journal Article
In: IEEE Access, vol. 12, pp. 55218-55224, 2024.
@article{cheng2024transfer,
title = {Transfer learning-assisted inverse modeling in nanophotonics based on mixture density networks},
author = {Liang Cheng and Prashant Singh and Francesco Ferranti},
url = {https://ieeexplore.ieee.org/abstract/document/10486893},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {IEEE Access},
volume = {12},
pages = {55218-55224},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Zhang, Tianru; Gupta, Ankit; Rodr'ıguez, Mar'ıa Andre'ına Francisco; Spjuth, Ola; Hellander, Andreas; Toor, Salman
Data management of scientific applications in a reinforcement learning-based
hierarchical storage system Journal Article
In: Expert Syst. Appl., vol. 237, no. Part B, pp. 121443, 2024.
@article{DBLP:journals/eswa/ZhangGRSHT24,
title = {Data management of scientific applications in a reinforcement learning-based
hierarchical storage system},
author = {Tianru Zhang and Ankit Gupta and Mar'ıa Andre'ına Francisco Rodr'ıguez and Ola Spjuth and Andreas Hellander and Salman Toor},
url = {https://doi.org/10.1016/j.eswa.2023.121443},
doi = {10.1016/J.ESWA.2023.121443},
year = {2024},
date = {2024-01-01},
journal = {Expert Syst. Appl.},
volume = {237},
number = {Part B},
pages = {121443},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Alawadi, Sadi; Ait-Mlouk, Addi; Toor, Salman; Hellander, Andreas
Toward efficient resource utilization at edge nodes in federated learning Journal Article
In: Progress in Artificial Intelligence, vol. 13, no. 2, pp. 101–117, 2024.
@article{alawadi2024toward,
title = {Toward efficient resource utilization at edge nodes in federated learning},
author = {Sadi Alawadi and Addi Ait-Mlouk and Salman Toor and Andreas Hellander},
year = {2024},
date = {2024-01-01},
journal = {Progress in Artificial Intelligence},
volume = {13},
number = {2},
pages = {101–117},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Gustafsson, Christian Jamtheim; Löfstedt, Tommy; Åkesson, Mattias; Rogowski, Viktor; Akbar, Muhammad Usman; Hellander, Andreas; Larsson, J Peter; Malmström, Annika; Blystad, Ida; Eklund, Anders
Federated training of segmentation models for radiation therapy treatment planning Journal Article
In: Radiotherapy and Oncology, vol. 194, pp. S4819–S4822, 2024.
@article{gustafsson2024federated,
title = {Federated training of segmentation models for radiation therapy treatment planning},
author = {Christian Jamtheim Gustafsson and Tommy Löfstedt and Mattias Åkesson and Viktor Rogowski and Muhammad Usman Akbar and Andreas Hellander and J Peter Larsson and Annika Malmström and Ida Blystad and Anders Eklund},
year = {2024},
date = {2024-01-01},
journal = {Radiotherapy and Oncology},
volume = {194},
pages = {S4819–S4822},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Li, Haoyuan; Toor, Salman
Empowering Data Mesh with Federated Learning Proceedings Article
In: 2024 IEEE International Conference on Big Data (BigData), pp. 2340–2342, IEEE 2024.
@inproceedings{li2024empowering,
title = {Empowering Data Mesh with Federated Learning},
author = {Haoyuan Li and Salman Toor},
year = {2024},
date = {2024-01-01},
booktitle = {2024 IEEE International Conference on Big Data (BigData)},
pages = {2340–2342},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Sun, Zhenlu; Teixeira, André MH; Toor, Salman
GNN-IDS: Graph neural network based intrusion detection system Proceedings Article
In: Proceedings of the 19th international conference on availability, reliability and security, pp. 1–12, 2024.
@inproceedings{sun2024gnn,
title = {GNN-IDS: Graph neural network based intrusion detection system},
author = {Zhenlu Sun and André MH Teixeira and Salman Toor},
year = {2024},
date = {2024-01-01},
booktitle = {Proceedings of the 19th international conference on availability, reliability and security},
pages = {1–12},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Al-Naday, Mays; Dobre, Vlad; Reed, Martin; Toor, Salman; Volckaert, Bruno; Turck, Filip De
Federated deep Q-learning networks for service-based anomaly detection and classification in edge-to-cloud ecosystems Journal Article
In: Annals of Telecommunications, vol. 79, no. 3, pp. 165–178, 2024.
@article{al2024federated,
title = {Federated deep Q-learning networks for service-based anomaly detection and classification in edge-to-cloud ecosystems},
author = {Mays Al-Naday and Vlad Dobre and Martin Reed and Salman Toor and Bruno Volckaert and Filip De Turck},
year = {2024},
date = {2024-01-01},
journal = {Annals of Telecommunications},
volume = {79},
number = {3},
pages = {165–178},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2023
Chu, Junjie; Singh, Prashant; Toor, Salman
Efficient Resource Scheduling for Distributed Infrastructures Using Negotiation Capabilities Proceedings Article
In: 2023 IEEE 16th International Conference on Cloud Computing (CLOUD), pp. 486–492, IEEE 2023.
@inproceedings{chu2023efficient,
title = {Efficient Resource Scheduling for Distributed Infrastructures Using Negotiation Capabilities},
author = {Junjie Chu and Prashant Singh and Salman Toor},
year = {2023},
date = {2023-01-01},
booktitle = {2023 IEEE 16th International Conference on Cloud Computing (CLOUD)},
pages = {486–492},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Zhang, Tianru; Hellander, Andreas; Toor, Salman
Efficient Hierarchical Storage Management Empowered by Reinforcement
Learning Journal Article
In: IEEE Trans. Knowl. Data Eng., vol. 35, no. 6, pp. 5780–5793, 2023.
@article{DBLP:journals/tkde/ZhangHT23,
title = {Efficient Hierarchical Storage Management Empowered by Reinforcement
Learning},
author = {Tianru Zhang and Andreas Hellander and Salman Toor},
url = {https://doi.org/10.1109/TKDE.2022.3176753},
doi = {10.1109/TKDE.2022.3176753},
year = {2023},
date = {2023-01-01},
journal = {IEEE Trans. Knowl. Data Eng.},
volume = {35},
number = {6},
pages = {5780–5793},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Zhang, Tianru; Hellander, Andreas; Toor, Salman
Efficient Hierarchical Storage Management Empowered by Reinforcement
Learning Extended Abstract Proceedings Article
In: 39th IEEE International Conference on Data Engineering, ICDE 2023,
Anaheim, CA, USA, April 3-7, 2023, pp. 3869–3870, IEEE, 2023.
@inproceedings{DBLP:conf/icde/ZhangHT23,
title = {Efficient Hierarchical Storage Management Empowered by Reinforcement
Learning Extended Abstract},
author = {Tianru Zhang and Andreas Hellander and Salman Toor},
url = {https://doi.org/10.1109/ICDE55515.2023.00361},
doi = {10.1109/ICDE55515.2023.00361},
year = {2023},
date = {2023-01-01},
booktitle = {39th IEEE International Conference on Data Engineering, ICDE 2023,
Anaheim, CA, USA, April 3-7, 2023},
pages = {3869–3870},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Ait-Mlouk, Addi; Alawadi, Sadi; Toor, Salman; Hellander, Andreas
FedBot: Enhancing Privacy in Chatbots with Federated Learning Journal Article
In: CoRR, vol. abs/2304.03228, 2023.
@article{DBLP:journals/corr/abs-2304-03228,
title = {FedBot: Enhancing Privacy in Chatbots with Federated Learning},
author = {Addi Ait-Mlouk and Sadi Alawadi and Salman Toor and Andreas Hellander},
url = {https://doi.org/10.48550/arXiv.2304.03228},
doi = {10.48550/ARXIV.2304.03228},
year = {2023},
date = {2023-01-01},
journal = {CoRR},
volume = {abs/2304.03228},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Alawadi, Sadi; Ait-Mlouk, Addi; Toor, Salman; Hellander, Andreas
Toward efficient resource utilization at edge nodes in federated learning Journal Article
In: CoRR, vol. abs/2309.10367, 2023.
@article{DBLP:journals/corr/abs-2309-10367,
title = {Toward efficient resource utilization at edge nodes in federated learning},
author = {Sadi Alawadi and Addi Ait-Mlouk and Salman Toor and Andreas Hellander},
url = {https://doi.org/10.48550/arXiv.2309.10367},
doi = {10.48550/ARXIV.2309.10367},
year = {2023},
date = {2023-01-01},
journal = {CoRR},
volume = {abs/2309.10367},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chu, Junjie; Singh, Prashant; Toor, Salman
Efficient Resource Scheduling for Distributed Infrastructures Using
Negotiation Capabilities Proceedings Article
In: 16th IEEE International Conference on Cloud Computing, CLOUD 2023,
Chicago, IL, USA, July 2-8, 2023, pp. 486–492, IEEE, 2023.
@inproceedings{DBLP:conf/IEEEcloud/ChuST23,
title = {Efficient Resource Scheduling for Distributed Infrastructures Using
Negotiation Capabilities},
author = {Junjie Chu and Prashant Singh and Salman Toor},
url = {https://doi.org/10.1109/CLOUD60044.2023.00065},
doi = {10.1109/CLOUD60044.2023.00065},
year = {2023},
date = {2023-01-01},
booktitle = {16th IEEE International Conference on Cloud Computing, CLOUD 2023,
Chicago, IL, USA, July 2-8, 2023},
pages = {486–492},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Al-Naday, Mays F.; Reed, Martin J.; Dobre, Vlad; Toor, Salman; Volckaert, Bruno; Turck, Filip De
Service-based Federated Deep Reinforcement Learning for Anomaly Detection
in Fog Ecosystems Proceedings Article
In: Lopez, Diego; Montpetit, Marie-José; Cerroni, Walter; Mauro, Mario Di; Borylo, Piotr (Ed.): 26th Conference on Innovation in Clouds, Internet and Networks, ICIN
2023, Paris, France, March 6-9, 2023, pp. 121–128, IEEE, 2023.
@inproceedings{DBLP:conf/icin/AlNadayRDTVT23,
title = {Service-based Federated Deep Reinforcement Learning for Anomaly Detection
in Fog Ecosystems},
author = {Mays F. Al-Naday and Martin J. Reed and Vlad Dobre and Salman Toor and Bruno Volckaert and Filip De Turck},
editor = {Diego Lopez and Marie-José Montpetit and Walter Cerroni and Mario Di Mauro and Piotr Borylo},
url = {https://doi.org/10.1109/ICIN56760.2023.10073495},
doi = {10.1109/ICIN56760.2023.10073495},
year = {2023},
date = {2023-01-01},
booktitle = {26th Conference on Innovation in Clouds, Internet and Networks, ICIN
2023, Paris, France, March 6-9, 2023},
pages = {121–128},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Mathias, Sonja; Adameyko, Igor; Hellander, Andreas; Kursawe, Jochen
Contributions of cell behavior to geometric order in embryonic cartilage Journal Article
In: PLoS Computational Biology, vol. 19, no. 11, pp. e1011658, 2023.
@article{mathias2023contributions,
title = {Contributions of cell behavior to geometric order in embryonic cartilage},
author = {Sonja Mathias and Igor Adameyko and Andreas Hellander and Jochen Kursawe},
year = {2023},
date = {2023-01-01},
journal = {PLoS Computational Biology},
volume = {19},
number = {11},
pages = {e1011658},
publisher = {Public Library of Science San Francisco, CA USA},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Zhang, Tianru; Hellander, Andreas; Toor, Salman
Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract Proceedings Article
In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 3869–3870, IEEE 2023.
@inproceedings{zhang2023efficient,
title = {Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract},
author = {Tianru Zhang and Andreas Hellander and Salman Toor},
year = {2023},
date = {2023-01-01},
booktitle = {2023 IEEE 39th International Conference on Data Engineering (ICDE)},
pages = {3869–3870},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2022
Jiang, Richard; Singh, Prashant; Wrede, Fredrik; Hellander, Andreas; Petzold, Linda
Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods Journal Article
In: PLoS computational biology, vol. 18, no. 1, pp. e1009830, 2022.
@article{jiang2022identification,
title = {Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods},
author = {Richard Jiang and Prashant Singh and Fredrik Wrede and Andreas Hellander and Linda Petzold},
year = {2022},
date = {2022-01-01},
journal = {PLoS computational biology},
volume = {18},
number = {1},
pages = {e1009830},
publisher = {Public Library of Science San Francisco, CA USA},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Coulier, Adrien; Singh, Prashant; Sturrock, Marc; Hellander, Andreas
Systematic comparison of modeling fidelity levels and parameter inference settings applied to negative feedback gene regulation Journal Article
In: PLOS Computational Biology, vol. 18, no. 12, pp. e1010683, 2022.
@article{coulier2022systematic,
title = {Systematic comparison of modeling fidelity levels and parameter inference settings applied to negative feedback gene regulation},
author = {Adrien Coulier and Prashant Singh and Marc Sturrock and Andreas Hellander},
year = {2022},
date = {2022-01-01},
journal = {PLOS Computational Biology},
volume = {18},
number = {12},
pages = {e1010683},
publisher = {Public Library of Science San Francisco, CA USA},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Wrede, Fredrik; Eriksson, Robin; Jiang, Richard; Petzold, Linda; Engblom, Stefan; Hellander, Andreas; Singh, Prashant
Robust and integrative Bayesian neural networks for likelihood-free parameter inference Proceedings Article
In: 2022 International Joint Conference on Neural Networks (IJCNN), pp. 1–10, IEEE 2022.
@inproceedings{wrede2022robust,
title = {Robust and integrative Bayesian neural networks for likelihood-free parameter inference},
author = {Fredrik Wrede and Robin Eriksson and Richard Jiang and Linda Petzold and Stefan Engblom and Andreas Hellander and Prashant Singh},
year = {2022},
date = {2022-01-01},
booktitle = {2022 International Joint Conference on Neural Networks (IJCNN)},
pages = {1–10},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Ekmefjord, Morgan; Ait-Mlouk, Addi; Alawadi, Sadi; Åkesson, Mattias; Singh, Prashant; Spjuth, Ola; Toor, Salman; Hellander, Andreas
Scalable federated machine learning with fedn Proceedings Article
In: 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pp. 555–564, IEEE 2022.
@inproceedings{ekmefjord2022scalable,
title = {Scalable federated machine learning with fedn},
author = {Morgan Ekmefjord and Addi Ait-Mlouk and Sadi Alawadi and Mattias Åkesson and Prashant Singh and Ola Spjuth and Salman Toor and Andreas Hellander},
year = {2022},
date = {2022-01-01},
booktitle = {2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid)},
pages = {555–564},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Javed, Omar; Singh, Prashant; Reger, Giles; Toor, Salman
To test, or not to test: A proactive approach for deciding complete performance test initiation Proceedings Article
In: 2022 IEEE International Conference on Big Data (Big Data), pp. 4758–4767, IEEE 2022.
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Mathias, Sonja; Coulier, Adrien; Hellander, Andreas
CBMOS: a GPU-enabled Python framework for the numerical study of
center-based models Journal Article
In: BMC Bioinform., vol. 23, no. 1, pp. 55, 2022.
@article{DBLP:journals/bmcbi/MathiasCH22,
title = {CBMOS: a GPU-enabled Python framework for the numerical study of
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Jiang, Richard M.; Singh, Prashant; Wrede, Fredrik; Hellander, Andreas; Petzold, Linda R.
Identification of dynamic mass-action biochemical reaction networks
using sparse Bayesian methods Journal Article
In: PLoS Comput. Biol., vol. 18, no. 1, 2022.
@article{DBLP:journals/ploscb/JiangSWHP22,
title = {Identification of dynamic mass-action biochemical reaction networks
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Coulier, Adrien; Singh, Prashant; Sturrock, Marc; Hellander, Andreas
Systematic comparison of modeling fidelity levels and parameter inference
settings applied to negative feedback gene regulation Journal Article
In: PLoS Comput. Biol., vol. 18, no. 12, pp. 1010683, 2022.
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title = {Systematic comparison of modeling fidelity levels and parameter inference
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Åkesson, Mattias; Singh, Prashant; Wrede, Fredrik; Hellander, Andreas
Convolutional Neural Networks as Summary Statistics for Approximate
Bayesian Computation Journal Article
In: IEEE ACM Trans. Comput. Biol. Bioinform., vol. 19, no. 6, pp. 3353–3365, 2022.
@article{DBLP:journals/tcbb/AkessonSWH22,
title = {Convolutional Neural Networks as Summary Statistics for Approximate
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author = {Mattias Åkesson and Prashant Singh and Fredrik Wrede and Andreas Hellander},
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doi = {10.1109/TCBB.2021.3108695},
year = {2022},
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Ekmefjord, Morgan; Ait-Mlouk, Addi; Alawadi, Sadi; Åkesson, Mattias; Singh, Prashant; Spjuth, Ola; Toor, Salman; Hellander, Andreas
Scalable federated machine learning with FEDn Proceedings Article
In: 22nd IEEE International Symposium on Cluster, Cloud and Internet
Computing, CCGrid 2022, Taormina, Italy, May 16-19, 2022, pp. 555–564, IEEE, 2022.
@inproceedings{DBLP:conf/ccgrid/EkmefjordAAASST22,
title = {Scalable federated machine learning with FEDn},
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Wrede, Fredrik; Eriksson, Robin; Jiang, Richard M.; Petzold, Linda R.; Engblom, Stefan; Hellander, Andreas; Singh, Prashant
Robust and integrative Bayesian neural networks for likelihood-free
parameter inference Proceedings Article
In: International Joint Conference on Neural Networks, IJCNN 2022, Padua,
Italy, July 18-23, 2022, pp. 1–10, IEEE, 2022.
@inproceedings{DBLP:conf/ijcnn/WredeEJPEHS22,
title = {Robust and integrative Bayesian neural networks for likelihood-free
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author = {Fredrik Wrede and Robin Eriksson and Richard M. Jiang and Linda R. Petzold and Stefan Engblom and Andreas Hellander and Prashant Singh},
url = {https://doi.org/10.1109/IJCNN55064.2022.9892800},
doi = {10.1109/IJCNN55064.2022.9892800},
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Zhang, Tianru; Toor, Salman; Hellander, Andreas
Efficient Hierarchical Storage Management Framework Empowered by Reinforcement
Learning Journal Article
In: CoRR, vol. abs/2201.11668, 2022.
@article{DBLP:journals/corr/abs-2201-11668,
title = {Efficient Hierarchical Storage Management Framework Empowered by Reinforcement
Learning},
author = {Tianru Zhang and Salman Toor and Andreas Hellander},
url = {https://arxiv.org/abs/2201.11668},
year = {2022},
date = {2022-01-01},
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Ait-Mlouk, Addi; Alawadi, Sadi; Toor, Salman; Hellander, Andreas
FedQAS: Privacy-aware machine reading comprehension with federated
learning Journal Article
In: CoRR, vol. abs/2202.04742, 2022.
@article{DBLP:journals/corr/abs-2202-04742,
title = {FedQAS: Privacy-aware machine reading comprehension with federated
learning},
author = {Addi Ait-Mlouk and Sadi Alawadi and Salman Toor and Andreas Hellander},
url = {https://arxiv.org/abs/2202.04742},
year = {2022},
date = {2022-01-01},
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Javed, Omar; Singh, Prashant; Reger, Giles; Toor, Salman
To test, or not to test: A proactive approach for deciding complete
performance test initiation Proceedings Article
In: Tsumoto, Shusaku; Ohsawa, Yukio; Chen, Lei; Poel, Dirk Van; Hu, Xiaohua; Motomura, Yoichi; Takagi, Takuya; Wu, Lingfei; Xie, Ying; Abe, Akihiro; Raghavan, Vijay (Ed.): IEEE International Conference on Big Data, Big Data 2022, Osaka,
Japan, December 17-20, 2022, pp. 4758–4767, IEEE, 2022.
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Javed, Omar; Singh, Prashant; Reger, Giles; Toor, Salman
To test, or not to test: A proactive approach for deciding complete
performance test initiation Journal Article
In: CoRR, vol. abs/2205.14749, 2022.
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title = {To test, or not to test: A proactive approach for deciding complete
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Clouard, Camille; Ausmees, Kristiina; Nettelblad, Carl
A joint use of pooling and imputation for genotyping SNPs Journal Article
In: BMC Bioinform., vol. 23, no. 1, pp. 421, 2022.
@article{DBLP:journals/bmcbi/ClouardAN22,
title = {A joint use of pooling and imputation for genotyping SNPs},
author = {Camille Clouard and Kristiina Ausmees and Carl Nettelblad},
url = {https://doi.org/10.1186/s12859-022-04974-7},
doi = {10.1186/S12859-022-04974-7},
year = {2022},
date = {2022-01-01},
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Kaucka, Marketa; Araus, Alberto Joven; Tesarova, Marketa; Currie, Joshua D; Boström, Johan; Kavkova, Michaela; Petersen, Julian; Yao, Zeyu; Bouchnita, Anass; Hellander, Andreas; others,
Altered developmental programs and oriented cell divisions lead to bulky bones during salamander limb regeneration Journal Article
In: Nature Communications, vol. 13, no. 1, pp. 6949, 2022.
@article{kaucka2022altered,
title = {Altered developmental programs and oriented cell divisions lead to bulky bones during salamander limb regeneration},
author = {Marketa Kaucka and Alberto Joven Araus and Marketa Tesarova and Joshua D Currie and Johan Boström and Michaela Kavkova and Julian Petersen and Zeyu Yao and Anass Bouchnita and Andreas Hellander and others},
year = {2022},
date = {2022-01-01},
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volume = {13},
number = {1},
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Bouderlique, Thibault; Petersen, Julian; Faure, Louis; Abed-Navandi, Daniel; Bouchnita, Anass; Mueller, Benjamin; Nazarov, Murtazo; Englmaier, Lukas; Tesarova, Marketa; Frade, Pedro R; others,
Surface flow for colonial integration in reef-building corals Journal Article
In: Current Biology, vol. 32, no. 12, pp. 2596–2609, 2022.
@article{bouderlique2022surface,
title = {Surface flow for colonial integration in reef-building corals},
author = {Thibault Bouderlique and Julian Petersen and Louis Faure and Daniel Abed-Navandi and Anass Bouchnita and Benjamin Mueller and Murtazo Nazarov and Lukas Englmaier and Marketa Tesarova and Pedro R Frade and others},
year = {2022},
date = {2022-01-01},
journal = {Current Biology},
volume = {32},
number = {12},
pages = {2596–2609},
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2021
Singh, Prashant; Wrede, Fredrik; Hellander, Andreas
Scalable machine learning-assisted model exploration and inference using Sciope Journal Article
In: Bioinformatics, vol. 37, no. 2, pp. 279–281, 2021.
@article{singh2021scalable,
title = {Scalable machine learning-assisted model exploration and inference using Sciope},
author = {Prashant Singh and Fredrik Wrede and Andreas Hellander},
year = {2021},
date = {2021-01-01},
journal = {Bioinformatics},
volume = {37},
number = {2},
pages = {279–281},
publisher = {Oxford University Press},
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Jiang, Richard; Jacob, Bruno; Geiger, Matthew; Matthew, Sean; Rumsey, Bryan; Singh, Prashant; Wrede, Fredrik; Yi, Tau-Mu; Drawert, Brian; Hellander, Andreas; others,
Epidemiological modeling in stochss live! Journal Article
In: Bioinformatics, vol. 37, no. 17, pp. 2787–2788, 2021.
@article{jiang2021epidemiological,
title = {Epidemiological modeling in stochss live!},
author = {Richard Jiang and Bruno Jacob and Matthew Geiger and Sean Matthew and Bryan Rumsey and Prashant Singh and Fredrik Wrede and Tau-Mu Yi and Brian Drawert and Andreas Hellander and others},
year = {2021},
date = {2021-01-01},
journal = {Bioinformatics},
volume = {37},
number = {17},
pages = {2787–2788},
publisher = {Oxford University Press},
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Akesson, Mattias; Singh, Prashant; Wrede, Fredrik; Hellander, Andreas
Convolutional neural networks as summary statistics for approximate bayesian computation Journal Article
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021.
@article{akesson2021convolutional,
title = {Convolutional neural networks as summary statistics for approximate bayesian computation},
author = {Mattias Akesson and Prashant Singh and Fredrik Wrede and Andreas Hellander},
year = {2021},
date = {2021-01-01},
journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
publisher = {IEEE},
keywords = {},
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Jiang, Richard M; Wrede, Fredrik; Singh, Prashant; Hellander, Andreas; Petzold, Linda R
Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators Journal Article
In: BMC bioinformatics, vol. 22, no. 1, pp. 339, 2021.
@article{jiang2021accelerated,
title = {Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators},
author = {Richard M Jiang and Fredrik Wrede and Prashant Singh and Andreas Hellander and Linda R Petzold},
year = {2021},
date = {2021-01-01},
journal = {BMC bioinformatics},
volume = {22},
number = {1},
pages = {339},
publisher = {BioMed Central London},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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