Connectionist Speaker Normalization with Generalized Resource Allocating Networks. - Cesare Furlanello; Diego Giuliani; Edmondo Trentin (NIPS, 1994)

Application of Generalized Radial Basis Functions In Speaker Normalization and Identification. - Cesare Furlanello; Diego Giuliani; Edmondo Trentin; Daniele Falavigna (ISCAS, 1995)

Speaker normalization with a mixture of recurrent networks. - Edmondo Trentin; Diego Giuliani (ESANN, 1997)

Speaker Normalization and Model Selection of Combined Neural Networks. - Cesare Furlanello; Diego Giuliani; Edmondo Trentin; Stefano Merler (Connect. Sci., 1997)

Estimating the crowding level with a neuro-fuzzy classifier. - Massimo Boninsegna; Tarcisio Coianiz; Edmondo Trentin (J. Electronic Imaging, 1997)

Activation functions with learnable amplitude. - Edmondo Trentin (IJCNN, 1999)

Learning Perception for Indoor Robot Navigation with a Hybrid Hidden Markov Model/Recurrent Neural Networks Approach. - Edmondo Trentin; Roldano Cattoni (Connect. Sci., 1999)

The Regularized SNN-TA Model for Recognition of Noisy Speech. - Edmondo Trentin; Marco Matassoni (IJCNN (5), 2000)

Continuous Speech Recognition with a Robust Connectionist/Markovian Hybrid Model. - Edmondo Trentin; Marco Gori (ICANN, 2001)

Toward noise-tolerant acoustic models. - Edmondo Trentin; Marco Gori (INTERSPEECH, 2001)

A survey of hybrid ANN/HMM models for automatic speech recognition. - Edmondo Trentin; Marco Gori (Neurocomputing, 2001)

A Mixture of Recurrent Neural Networks for Speaker Normalisation. - Edmondo Trentin; Diego Giuliani (Neural Comput. Appl., 2001)

Networks with trainable amplitude of activation functions. - Edmondo Trentin (Neural Networks, 2001)

Toward a modular connectionist model of local chlorophyll concentration from satellite images. - Edmondo Trentin; Letizia Magnoni; Alfio Andronico (IJCNN, 2003)

Evaluation on the Aurora 2 database of acoustic models that are less noise-sensitive. - Edmondo Trentin; Marco Matassoni; Marco Gori (INTERSPEECH, 2003)

Nonparametric Hidden Markov Models: Principles and Applications to Speech Recognition. - Edmondo Trentin (WIRN, 2003)

Noise-tolerant speech recognition: the SNN-TA approach. - Edmondo Trentin; Marco Matassoni (Inf. Sci., 2003)

Robust combination of neural networks and hidden Markov models for speech recognition. - Edmondo Trentin; Marco Gori (IEEE Trans. Neural Networks, 2003)

Feature Normalization via ANN/HMM Inversion for Speech Recognition Under Noisy Conditions. - Edmondo Trentin; Marco Gori (MMSP, 2005)

Simple and Effective Connectionist Nonparametric Estimation of Probability Density Functions. - Edmondo Trentin (ANNPR, 2006)

A Novel Connectionist-Oriented Feature Normalization Technique. - Edmondo Trentin (ICANN (2), 2006)

Inversion-based nonlinear adaptation of noisy acoustic parameters for a neural/HMM speech recognizer. - Edmondo Trentin; Marco Gori (Neurocomputing, 2006)

Unbiased SVM Density Estimation with Application to Graphical Pattern Recognition. - Edmondo Trentin; Ernesto Di Iorio (ICANN (2), 2007)

A Simple and Effective Neural Model for the Classification of Structured Patterns. - Edmondo Trentin; Ernesto Di Iorio (KES (1), 2007)

Neural-based downlink scheduling algorithm for broadband wireless networks. - Pasquale Fiengo; Giovanni Giambene; Edmondo Trentin (Comput. Commun., 2007)

Classification of molecular structures made easy. - Edmondo Trentin; Ernesto Di Iorio (IJCNN, 2008)

A Maximum-Likelihood Connectionist Model for Unsupervised Learning over Graphical Domains. - Edmondo Trentin; Leonardo Rigutini (ICANN (1), 2009)

Scalable statistical learning: A modular bayesian/markov network approach. - Antonino Freno; Edmondo Trentin; Marco Gori (IJCNN, 2009)

Unsupervised nonparametric density estimation: A neural network approach. - Edmondo Trentin; Antonino Freno (IJCNN, 2009)

Scalable pseudo-likelihood estimation in hybrid random fields. - Antonino Freno; Edmondo Trentin; Marco Gori (KDD, 2009)

Classification of graphical data made easy. - Edmondo Trentin; Ernesto Di Iorio (Neurocomputing, 2009)

A hybrid random field model for scalable statistical learning. - Antonino Freno; Edmondo Trentin; Marco Gori (Neural Networks, 2009)

Probabilistic Interpretation of Neural Networks for the Classification of Vectors, Sequences and Graphs. - Edmondo Trentin; Antonino Freno (Innovations in Neural Information Paradigms and Applications, 2009)

Maximum Echo-State-Likelihood Networks for Emotion Recognition. - Edmondo Trentin; Stefan Scherer; Friedhelm Schwenker (ANNPR, 2010)

Recognition of Sequences of Graphical Patterns. - Edmondo Trentin; Shujia Zhang; Markus Hagenbuchner (ANNPR, 2010)

Kernel-Based Hybrid Random Fields for Nonparametric Density Estimation. - Antonino Freno; Edmondo Trentin; Marco Gori (ECAI, 2010)

Supervised and Unsupervised Co-training of Adaptive Activation Functions in Neural Nets. - Ilaria Castelli; Edmondo Trentin (PSL, 2011)

Semi-unsupervised Weighted Maximum-Likelihood Estimation of Joint Densities for the Co-training of Adaptive Activation Functions. - Ilaria Castelli; Edmondo Trentin (PSL, 2011)

Comparison of Combined Probabilistic Connectionist Models in a Forensic Application. - Edmondo Trentin; Luca Lusnig; Fabio Cavalli (PSL, 2011)

Hybrid Random Fields - A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models - Antonino Freno; Edmondo Trentin (Springer, 2011)

Towards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation. - Marco Bongini; Edmondo Trentin (ANNPR, 2012)

Towards a Novel Probabilistic Graphical Model of Sequential Data: Fundamental Notions and a Solution to the Problem of Parameter Learning. - Edmondo Trentin; Marco Bongini (ANNPR, 2012)

Hidden Markov models with graph densities for action recognition. - Michael Glodek; Edmondo Trentin; Friedhelm Schwenker; Günther Palm (IJCNN, 2013)

Combination of supervised and unsupervised learning for training the activation functions of neural networks. - Ilaria Castelli; Edmondo Trentin (Pattern Recognit. Lett., 2014)

Partially supervised learning for pattern recognition. - Friedhelm Schwenker; Edmondo Trentin (Pattern Recognit. Lett., 2014)

Pattern classification and clustering: A review of partially supervised learning approaches. - Friedhelm Schwenker; Edmondo Trentin (Pattern Recognit. Lett., 2014)

Techniques for dealing with incomplete data: a tutorial and survey. - Marco Aste; Massimo Boninsegna; Antonino Freno; Edmondo Trentin (Pattern Anal. Appl., 2015)

Maximum-likelihood normalization of features increases the robustness of neural-based spoken human-computer interaction. - Edmondo Trentin (Pattern Recognit. Lett., 2015)

Emotion recognition from speech signals via a probabilistic echo-state network. - Edmondo Trentin; Stefan Scherer; Friedhelm Schwenker (Pattern Recognit. Lett., 2015)

A Hybrid Recurrent Neural Network/Dynamic Probabilistic Graphical Model Predictor of the Disulfide Bonding State of Cysteines from the Primary Structure of Proteins. - Marco Bongini; Vincenzo Laveglia; Edmondo Trentin (ANNPR, 2016)

Soft-Constrained Nonparametric Density Estimation with Artificial Neural Networks. - Edmondo Trentin (ANNPR, 2016)

A Refinement Algorithm for Deep Learning via Error-Driven Propagation of Target Outputs. - Vincenzo Laveglia; Edmondo Trentin (ANNPR, 2018)

Maximum-Likelihood Estimation of Neural Mixture Densities: Model, Algorithm, and Preliminary Experimental Evaluation. - Edmondo Trentin (ANNPR, 2018)

Nonparametric small random networks for graph-structured pattern recognition. - Edmondo Trentin; Ernesto Di Iorio (Neurocomputing, 2018)

Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology. - Edmondo Trentin; Luca Lusnig; Fabio Cavalli (Neural Networks, 2018)

Dynamic Hybrid Random Fields for the Probabilistic Graphical Modeling of Sequential Data: Definitions, Algorithms, and an Application to Bioinformatics. - Marco Bongini; Antonino Freno; Vincenzo Laveglia; Edmondo Trentin (Neural Process. Lett., 2018)

Soft-Constrained Neural Networks for Nonparametric Density Estimation. - Edmondo Trentin (Neural Process. Lett., 2018)

Off the Mainstream: Advances in Neural Networks and Machine Learning for Pattern Recognition. - Edmondo Trentin; Friedhelm Schwenker; Neamat El Gayar; Hazem M. Abbas (Neural Process. Lett., 2018)

Recursive Neural Networks for Density Estimation Over Generalized Random Graphs. - Marco Bongini; Leonardo Rigutini; Edmondo Trentin (IEEE Trans. Neural Networks Learn. Syst., 2018)

Mixtures of Deep Neural Experts for Automated Speech Scoring. - Sara Papi; Edmondo Trentin; Roberto Gretter; Marco Matassoni; Daniele Falavigna (INTERSPEECH, 2020)

A Novel Representation of Graphical Patterns for Graph Convolution Networks. - Marco Benini; Pietro Bongini; Edmondo Trentin (ANNPR, 2022)

Downward-Growing Neural Networks. - Vincenzo Laveglia; Edmondo Trentin (Entropy, 2023)

Multivariate Density Estimation with Deep Neural Mixture Models. - Edmondo Trentin (Neural Process. Lett., 2023)

Gaussian-Mixture Neural Networks. - Duccio Meconcelli; Edmondo Trentin (ANNPR, 2024)

Automatic Interpretation of 18F-Fluorocholine PET/CT Findings in Patients with Primary Hyperparathyroidism: A Novel Dataset with Benchmarks. - Natasha Sharma; Sona Balogova; Lucia Noskovicova; Françoise Montravers; Jean-Noël Talbot; Edmondo Trentin (ANNPR, 2024)

GrapHisto: A Robust Representation of Graph-Structured Data for Graph Convolutional Networks. - Marco Benini; Pietro Bongini; Edmondo Trentin (Neural Process. Lett., 2025)

Employing Discrete Fourier Transform in Representational Learning. - Raoof HojatJalali; Edmondo Trentin (CoRR, 2025)