Marco Ancona

O2 Czech Republic (Czechia) — Czech Republic

Computer Science · Physical Sciences

7h-index855citations13works0.02yr avg
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Research Topics

Adversarial Robustness in Machine Learning(6), Domain Adaptation and Few-Shot Learning(5), Explainable Artificial Intelligence (XAI)(5), Neural Networks and Applications(2), Advanced Neural Network Applications(1)

Publications13 total

InCytokine, an Open-Source Software, Reveals a TREM2 Variant-Specific Cytokine Signature
International Journal of Molecular Sciences·2026Open Access
Ovo, an Open-Source Ecosystem for De Novo Protein Design
2025Open Access
InCytokine, an open-source software, reveals a TREM2 variant specific cytokine signature
2025Open Access
A machine learning strategy for the identification of key <i>in silico</i> descriptors and prediction models for IgG monoclonal antibody developability properties
mAbs·2023· 36 citedOpen Access
Shapley Value as Principled Metric for Structured Network Pruning
arXiv (Cornell University)·2020· 6 citedOpen Access
Attribution Methods for Interpreting and Optimizing Deep Neural Networks
Repository for Publications and Research Data (ETH Zurich)·2020Open Access
MineTime Insight: Visualizing Meeting Habits to Promote Informed Scheduling Decisions
IEEE Transactions on Visualization and Computer Graphics·2019· 3 cited
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation
arXiv (Cornell University)·2019· 49 citedOpen Access
Gradient-Based Attribution Methods
Lecture notes in computer science·2019· 226 cited
Towards better understanding of gradient-based attribution methods for Deep Neural Networks
Repository for Publications and Research Data (ETH Zurich)·2018· 385 citedOpen Access
Towards better understanding of gradient-based attribution methods for Deep Neural Networks
arXiv (Cornell University)·2017· 30 citedOpen Access
A unified view of gradient-based attribution methods for Deep Neural Networks
arXiv (Cornell University)·2017· 110 citedOpen Access
Architecture for large microelectronic supervised learning artificial neural networks using a hybrid digital-analog approach
Neural Networks·1988· 10 cited

Frequent Co-authors

Markus Groß(7), Cengiz Öztireli(6), Enea Ceolini(4), Danny A. Bitton(4), David Příhoda(2), Deepak Kumar Jha(2), Sonia L. Farmer(2), Martin Vagenknecht(2), Alejandro Vázquez-Otero(2), Jindřich Soukup(2), Rebecca Mathew(2), Vanessa M. Peterson(2), Andrew B. Waight(1), Rojan Shrestha(1), Kevin J. Metcalf(1), Marc Bailly(1), Talal Widatalla(1), Zachary A. Rollins(1), Alan C. Cheng(1), Laurence Fayadat‐Dilman(1)