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María Rodríguez Martínez
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2020 – today
- 2024
- [j12]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
- [j11]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
- [j10]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) - [j9]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) - [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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last updated on 2024-08-10 01:27 CEST by the dblp team
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