María Rodríguez Martínez
- On quantitative aspects of model interpretability
2020/07/15 by An-phi Nguyen, María Rodríguez Martínez, Nguyen, An-phi +1 · 7 citations
Computer Science · #Data Stream Mining Techniques #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Aligned Diffusion Schrödinger Bridges
2023/02/22 by Vignesh Ram Somnath, Matteo Pariset, Somnath, Vignesh Ram +9 · 8 citations
Biochemistry, Genetics and Molecular Biology · #Cell Image Analysis Techniques #FOS: Biological sciences #FOS: Computer and information sciences #Fractal and DNA sequence analysis #Gene Regulatory Network Analysis #Machine Learning (cs.LG) #Quantitative Methods (q-bio.QM)
- Conformal Autoregressive Generation: Beam Search with Coverage Guarantees
2023/09/07 by Nicolas Deutschmann, Marvin Alberts, Deutschmann, Nicolas +3 · 4 citations
Computer Science · Biochemistry, Genetics and Molecular Biology · #Advanced Multi-Objective Optimization Algorithms #Advanced Image and Video Retrieval Techniques #Genomics and Chromatin Dynamics
- MonoNet: Towards Interpretable Models by Learning Monotonic Features
2019/09/30 by An-phi Nguyen, María Rodríguez Martínez, Nguyen, An-phi +1 · 3 citations
Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare
- Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks
2020/12/05 by Modestas Filipavicius, Matteo Manica, Filipavicius, Modestas +5 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · #Biomolecules (q-bio.BM) #Computation and Language (cs.CL) #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning in Bioinformatics #RNA and protein synthesis mechanisms #Topic Modeling #vaccines and immunoinformatics approaches