World's Best Scientists 2026 revealed!
Paolo Frasconi

Paolo Frasconi

D-Index & Metrics

Computer Science

D-Index
49
Citations
21541
World Ranking
5745
National Ranking
131

Overview

Paolo Frasconi is affiliated with the University of Florence in Italy. Their research spans multiple disciplines, with a primary focus on Medicine and Computer Science. These fields intersect notably in studies related to Cardiology and Cardiovascular Medicine as well as Biophysics, Signal Processing, Radiology, Nuclear Medicine and Imaging, and Artificial Intelligence.

The scientist's work covers several main topics. These include:

  • Atrial Fibrillation Management and Outcomes
  • Cell Image Analysis Techniques
  • Machine Learning and Data Classification
  • Music and Audio Processing
  • Advanced Fluorescence Microscopy Techniques
  • Single-cell and Spatial Transcriptomics
  • Venous Thromboembolism Diagnosis and Management

Recent publications by Paolo Frasconi reflect a variety of research areas and collaborations. Selected papers include:

  • "Universal autofocus for quantitative volumetric microscopy of whole mouse brains," 2021, Nature Methods
  • "Machine learning approach for prediction of outcomes in anticoagulated patients with atrial fibrillation," 2024, International Journal of Cardiology
  • "Deep learning-based localization algorithms on fluorescence human brain 3D reconstruction: a comparative study using stereology as a reference," 2024, Scientific Reports
  • "Two-Dimensional Aortic Size Normalcy: A Novelty Detection Approach," 2021, Diagnostics
  • "Hyperparameter Optimization in Machine Learning," 2024, arXiv (Cornell University)

The venues where Paolo Frasconi frequently publishes include:

  • International Journal of Cardiology
  • arXiv (Cornell University)
  • Nature Methods
  • Scientific Reports
  • Foundations and Trends® in Machine Learning

Collaboration plays a notable role in their research activities. Frequent co-authors are:

  • Luca Bindini
  • Andrea Bernardini
  • Martina Berteotti
  • Betti Giusti
  • Rossella Marcucci

Best Publications

  • Learning long-term dependencies with gradient descent is difficult

    Y. Bengio;P. Simard;P. Frasconi

  • Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning

    M. Lippi;M. Bertini;P. Frasconi

  • Exploiting the past and the future in protein secondary structure prediction.

    Pierre Baldi;Søren Brunak;Paolo Frasconi;Giovanni Soda

  • A general framework for adaptive processing of data structures

    P. Frasconi;M. Gori;A. Sperduti

  • Modeling the Internet and the Web

    Pierre Baldi;Paolo Frasconi;Padhraic Smyth

  • An Input Output HMM Architecture

    Yoshua Bengio;Paolo Frasconi

  • Input-output HMMs for sequence processing

    Y. Bengio;P. Frasconi

  • Modeling the Internet and the Web: Probabilistic Method and Algorithms

    Pierre Baldi;Paolo Frasconi;Padhraic Smyth

  • Learning without local minima in radial basis function networks

    M. Bianchini;P. Frasconi;M. Gori

  • The problem of learning long-term dependencies in recurrent networks

    Y. Bengio;P. Frasconi;P. Simard

  • Bilevel Programming for Hyperparameter Optimization and Meta-Learning

    Luca Franceschi;Paolo Frasconi;Saverio Salzo;Riccardo Grazzi

  • Local feedback multilayered networks

    Paolo Frasconi;Marco Gori;Giovanni Soda

  • New results on error correcting output codes of kernel machines

    A. Passerini;M. Pontil;P. Frasconi

  • Disulfide connectivity prediction using recursive neural networks and evolutionary information

    Alessandro Vullo;Paolo Frasconi

  • Forward and Reverse Gradient-Based Hyperparameter Optimization

    Luca Franceschi;Michele Donini;Paolo Frasconi;Massimiliano Pontil

  • Hidden tree Markov models for document image classification

    M. Diligenti;P. Frasconi;M. Gori

  • Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines

    Yuan Yao;Gian Luca Marcialis;Massimiliano Pontil;Massimiliano Pontil;Paolo Frasconi

  • Whole-Brain Vasculature Reconstruction at the Single Capillary Level.

    Antonino Paolo Di Giovanna;Alessandro Tibo;Ludovico Silvestri;Ludovico Silvestri;Marie Caroline Müllenbroich;Marie Caroline Müllenbroich

  • Representation of finite state automata in recurrent radial basis function networks

    Paolo Frasconi;Marco Gori;Marco Maggini;Giovanni Soda

  • kFOIL: learning simple relational kernels

    Niels Landwehr;Andrea Passerini;Luc De Raedt;Paolo Frasconi

  • Unified integration of explicit knowledge and learning by example in recurrent networks

    P. Frasconi;M. Gori;M. Maggini;G. Soda

Frequent Co-Authors

Marco Gori
Marco Gori University of Siena
Massimiliano Pontil
Massimiliano Pontil Italian Institute of Technology
Luc De Raedt
Luc De Raedt KU Leuven
Pierre Baldi
Pierre Baldi University of California, Irvine
Padhraic Smyth
Padhraic Smyth University of California, Irvine
Yoshua Bengio
Yoshua Bengio University of Montreal
Alessandro Sperduti
Alessandro Sperduti University of Padua
Gianluca Pollastri
Gianluca Pollastri University College Dublin
Gian Luca Marcialis
Gian Luca Marcialis University of Cagliari
Patrick Sturt
Patrick Sturt University of Edinburgh

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

If you're considering a career in computer science, there are various educational pathways to fit different goals and budgets. Exploring the fastest masters degree online options can help you accelerate your journey and enter the workforce sooner. These programs are designed for students who want to upskill quickly and efficiently.

For those focused on career advancement, choosing one of the most useful masters degrees can increase your job prospects and potential earnings. Specializations in tech-related fields like data science or cybersecurity are highly sought after by employers.

If you’re just starting out or prefer a shorter commitment, pursuing an associate's degree online offers a flexible and cost-effective way to gain essential computer science skills. These programs can also serve as a stepping stone toward a bachelor’s degree.

Budget-conscious students can further explore the cheapest online college options to keep tuition costs manageable. Whether you choose a fast-tracked master’s or an associate program, online degrees offer numerous pathways to launch or advance your computer science career.

Best Scientists Citing Paolo Frasconi

Trending Scientists