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ORCIDMaría Rodríguez Martínez
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2020 – today
- 2024
[j13]Nicolas Deutschmann, Mattia Rigotti, María Rodríguez Martínez:
Adaptive Conformal Regression with Split-Jackknife+ Scores. Trans. Mach. Learn. Res. 2024 (2024)- [c6]Nicolas Deutschmann, Marvin Alberts, María Rodríguez Martínez:
Conformal Autoregressive Generation: Beam Search with Coverage Guarantees. AAAI 2024: 11775-11783 - [i21]Ling Han, Hao Huang, Dustin Scheinost
, Mary-Anne Hartley, María Rodríguez Martínez:
Unlearning Information Bottleneck: Machine Unlearning of Systematic Patterns and Biases. CoRR abs/2405.14020 (2024) - 2023
- [j12]An-phi Nguyen, Stefania Vasilaki, María Rodríguez Martínez:
FLAN: feature-wise latent additive neural models for biological applications. Briefings Bioinform. 24(3) (2023) - [c5]Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne:
Aligned Diffusion Schrödinger Bridges. UAI 2023: 1985-1995 - [i20]Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne:
Aligned Diffusion Schrödinger Bridges. CoRR abs/2302.11419 (2023) - [i19]Nicolas Deutschmann, Mattia Rigotti, María Rodríguez Martínez:
Adaptive Conformal Regression with Jackknife+ Rescaled Scores. CoRR abs/2305.19901 (2023) - [i18]Nicolas Deutschmann, Marvin Alberts, María Rodríguez Martínez:
Conformal Autoregressive Generation: Beam Search with Coverage Guarantees. CoRR abs/2309.03797 (2023) - [i17]Vignesh Ram Somnath, Pier Giuseppe Sessa, María Rodríguez Martínez, Andreas Krause:
DockGame: Cooperative Games for Multimeric Rigid Protein Docking. CoRR abs/2310.06177 (2023) - 2022
- [j11]Varun S. Sharma, Andrea Fossati, Rodolfo Ciuffa, Marija Buljan, Evan G. Williams, Zhen Chen, Wenguang Shao, Patrick G. A. Pedrioli, Anthony W. Purcell, María Rodríguez Martínez, Jiangning Song, Matteo Manica, Ruedi Aebersold, Chen Li:
PCfun: a hybrid computational framework for systematic characterization of protein complex function. Briefings Bioinform. 23(4) (2022) - [j10]Anna Niarakis, Juilee Thakar, Matteo Barberis, María Rodríguez Martínez, Tomás Helikar, Marc R. Birtwistle, Claudine Chaouiya, Laurence Calzone, Andreas Dräger:
Computational modelling in health and disease: highlights of the 6th annual SysMod meeting. Bioinform. 38(21): 4990-4993 (2022) - [j9]Iliana Papadopoulou, An-Phi Nguyen, Anna Weber, María Rodríguez Martínez:
DECODE: a computational pipeline to discover T cell receptor binding rules. Bioinform. 38(Supplement_1): i246-i254 (2022) - [c4]Mara Graziani, Niccolò Marini, Nicolas Deutschmann, Nikita Janakarajan, Henning Müller, María Rodríguez Martínez:
Attention-Based Interpretable Regression of Gene Expression in Histology. iMIMIC@MICCAI 2022: 44-60 - [c3]Jonathan Haab, Nicolas Deutschmann, María Rodríguez Martínez:
Is Attention Interpretation? A Quantitative Assessment on Sets. PKDD/ECML Workshops (1) 2022: 303-321 - [i16]Jonathan Haab, Nicolas Deutschmann, María Rodríguez Martínez:
Is Attention Interpretation? A Quantitative Assessment On Sets. CoRR abs/2207.13018 (2022) - [i15]Mara Graziani, Niccolò Marini, Nicolas Deutschmann, Nikita Janakarajan, Henning Müller, María Rodríguez Martínez:
Attention-based Interpretable Regression of Gene Expression in Histology. CoRR abs/2208.13776 (2022) - 2021
- [j8]Andreas Dräger, Tomás Helikar, Matteo Barberis, Marc R. Birtwistle, Laurence Calzone, Claudine Chaouiya, Jan Hasenauer, Jonathan R. Karr, Anna Niarakis, María Rodríguez Martínez, Julio Saez-Rodriguez, Juilee Thakar:
SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems. Bioinform. 37(21): 3702-3706 (2021) - [j7]Anna Weber, Jannis Born, María Rodríguez Martínez:
TITAN: T-cell receptor specificity prediction with bimodal attention networks. Bioinform. 37(Supplement): 237-244 (2021) - [j6]Joris Cadow, Matteo Manica, Roland Mathis, Tiannan Guo, Ruedi Aebersold, María Rodríguez Martínez:
On the feasibility of deep learning applications using raw mass spectrometry data. Bioinform. 37(Supplement): 245-253 (2021) - [j5]Jannis Born, Matteo Manica, Joris Cadow, Greta Markert, Nil Adell Mill, Modestas Filipavicius, Nikita Janakarajan, Antonio Cardinale, Teodoro Laino, María Rodríguez Martínez:
Data-driven molecular design for discovery and synthesis of novel ligands: a case study on SARS-CoV-2. Mach. Learn. Sci. Technol. 2(2): 25024 (2021) - [j4]Cristian Axenie, Roman Bauer, María Rodríguez Martínez:
The Multiple Dimensions of Networks in Cancer: A Perspective. Symmetry 13(9): 1559 (2021) - [i14]Anna Weber, Jannis Born, María Rodríguez Martínez:
TITAN: T Cell Receptor Specificity Prediction with Bimodal Attention Networks. CoRR abs/2105.03323 (2021) - [i13]An-phi Nguyen, María Rodríguez Martínez:
It's FLAN time! Summing feature-wise latent representations for interpretability. CoRR abs/2106.10086 (2021) - 2020
- [j3]Joris Cadow, Jannis Born, Matteo Manica, Ali Oskooei, María Rodríguez Martínez:
PaccMann: a web service for interpretable anticancer compound sensitivity prediction. Nucleic Acids Res. 48(Webserver-Issue): W502-W508 (2020) - [j2]Matteo Manica, Raphael Polig, Mitra Purandare, Roland Mathis, Christoph Hagleitner, María Rodríguez Martínez:
FPGA Accelerated Analysis of Boolean Gene Regulatory Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 17(6): 2141-2147 (2020) - [c2]Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, María Rodríguez Martínez:
PaccMannRL: Designing Anticancer Drugs From Transcriptomic Data via Reinforcement Learning. RECOMB 2020: 231-233 - [e1]George Bebis, Max A. Alekseyev, Heyrim Cho, Jana Gevertz, María Rodríguez Martínez:
Mathematical and Computational Oncology - Second International Symposium, ISMCO 2020, San Diego, CA, USA, October 8-10, 2020, Proceedings. Lecture Notes in Computer Science 12508, Springer 2020, ISBN 978-3-030-64510-6 [contents] - [i12]Jannis Born, Matteo Manica, Joris Cadow, Greta Markert, Nil Adell Mill, Modestas Filipavicius, María Rodríguez Martínez:
PaccMannRL on SARS-CoV-2: Designing antiviral candidates with conditional generative models. CoRR abs/2005.13285 (2020) - [i11]An-phi Nguyen, María Rodríguez Martínez:
On quantitative aspects of model interpretability. CoRR abs/2007.07584 (2020) - [i10]An-phi Nguyen, María Rodríguez Martínez:
Learning Invariances for Interpretability using Supervised VAE. CoRR abs/2007.07591 (2020) - [i9]Modestas Filipavicius, Matteo Manica, Joris Cadow, María Rodríguez Martínez:
Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks. CoRR abs/2012.03084 (2020)
2010 – 2019
- 2019
- [j1]Matteo Manica, Roland Mathis, Joris Cadow, María Rodríguez Martínez:
Context-specific interaction networks from vector representation of words. Nat. Mach. Intell. 1(4): 181-190 (2019) - [i8]Guillaume Jaume, An-phi Nguyen, María Rodríguez Martínez, Jean-Philippe Thiran, Maria Gabrani:
edGNN: a Simple and Powerful GNN for Directed Labeled Graphs. CoRR abs/1904.08745 (2019) - [i7]Matteo Manica, Ali Oskooei, Jannis Born, Vigneshwari Subramanian, Julio Sáez-Rodríguez, María Rodríguez Martínez:
Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders. CoRR abs/1904.11223 (2019) - [i6]Jannis Born, Matteo Manica, Ali Oskooei, María Rodríguez Martínez:
Reinforcement learning-driven de-novo design of anticancer compounds conditioned on biomolecular profiles. CoRR abs/1909.05114 (2019) - [i5]An-phi Nguyen, María Rodríguez Martínez:
MonoNet: Towards Interpretable Models by Learning Monotonic Features. CoRR abs/1909.13611 (2019) - [i4]Ali Oskooei, Sophie Mai Chau, Jonas R. M. Weiss, Arvind Sridhar, María Rodríguez Martínez, Bruno Michel:
DeStress: Deep Learning for Unsupervised Identification of Mental Stress in Firefighters from Heart-rate Variability (HRV) Data. CoRR abs/1911.13213 (2019) - 2018
- [i3]Ali Oskooei, Matteo Manica, Roland Mathis, María Rodríguez Martínez:
Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer. CoRR abs/1808.06603 (2018) - [i2]Ali Oskooei, Jannis Born, Matteo Manica, Vigneshwari Subramanian, Julio Sáez-Rodríguez, María Rodríguez Martínez:
PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks. CoRR abs/1811.06802 (2018) - [i1]Bianca-Cristina Cristescu, Zalán Borsos, John Lygeros, María Rodríguez Martínez, Maria Anna Rapsomaniki:
Inference of the three-dimensional chromatin structure and its temporal behavior. CoRR abs/1811.09619 (2018) - 2016
- [c1]Lukas Studer, Loïc Paulevé, Christoph Zechner, Matthias Reumann, María Rodríguez Martínez, Heinz Koeppl:
Marginalized Continuous Time Bayesian Networks for Network Reconstruction from Incomplete Observations. AAAI 2016: 2051-2057
Coauthor Index
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