Maurizio Filippone

According to our database1, Maurizio Filippone authored at least 78 papers between 2004 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2021
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
All You Need is a Good Functional Prior for Bayesian Deep Learning.
CoRR, 2020

Sparse within Sparse Gaussian Processes using Neighbor Information.
CoRR, 2020

Learning Optimal Conditional Priors For Disentangled Representations.
CoRR, 2020

Isotropic SGD: a Practical Approach to Bayesian Posterior Sampling.
CoRR, 2020

A Variational View on Bootstrap Ensembles as Bayesian Inference.
CoRR, 2020

Rethinking Sparse Gaussian Processes: Bayesian Approaches to Inducing-Variable Approximations.
CoRR, 2020

A comparative evaluation of novelty detection algorithms for discrete sequences.
Artif. Intell. Rev., 2020

Model Monitoring and Dynamic Model Selection in Travel Time-Series Forecasting.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

Walsh-Hadamard Variational Inference for Bayesian Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

LIBRE: Learning Interpretable Boolean Rule Ensembles.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease.
NeuroImage, 2019

Efficient Approximate Inference with Walsh-Hadamard Variational Inference.
CoRR, 2019

Sparsification as a Remedy for Staleness in Distributed Asynchronous SGD.
CoRR, 2019

Exact gaussian process regression with distributed computations.
Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 2019

Pseudo-Extended Markov chain Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Good Initializations of Variational Bayes for Deep Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

Calibrating Deep Convolutional Gaussian Processes.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A comparative evaluation of outlier detection algorithms: Experiments and analyses.
Pattern Recognit., 2018

Deep Gaussian Process autoencoders for novelty detection.
Mach. Learn., 2018

Statistical inference in mechanistic models: time warping for improved gradient matching.
Comput. Stat., 2018

Variational Calibration of Computer Models.
CoRR, 2018

Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Constraining the Dynamics of Deep Probabilistic Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

Team Deep Neural Networks for Interference Channels.
Proceedings of the 2018 IEEE International Conference on Communications Workshops, 2018

2017
Decentralized Deep Scheduling for Interference Channels.
CoRR, 2017

AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Bayesian Inference of Log Determinants.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Entropic Trace Estimates for Log Determinants.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Mini-batch spectral clustering.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Random Feature Expansions for Deep Gaussian Processes.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Mini-Batch Spectral Clustering.
CoRR, 2016

Looking Good With Flickr Faves: Gaussian Processes for Finding Difference Makers in Personality Impressions.
Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Preconditioning Kernel Matrices.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Inference in a Partial Differential Equations Model of Pulmonary Arterial and Venous Blood Circulation Using Statistical Emulation.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2016

Parameter Inference in Differential Equation Models of Biopathways Using Time Warped Gradient Matching.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2016

2015
On User Availability Prediction and Network Applications.
IEEE/ACM Trans. Netw., 2015

MCMC for Variationally Sparse Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE).
Proceedings of the 32nd International Conference on Machine Learning, 2015

Monte Carlo Strength Evaluation: Fast and Reliable Password Checking.
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015

2014
Predicting Continuous Conflict Perceptionwith Bayesian Gaussian Processes.
IEEE Trans. Affect. Comput., 2014

Pseudo-Marginal Bayesian Inference for Gaussian Processes.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

2013
Editorial A Successful Change From TNN to TNNLS and a Very Successful Year.
IEEE Trans. Neural Networks Learn. Syst., 2013

Aggregation Algorithm Towards Large-Scale Boolean Network Analysis.
IEEE Trans. Autom. Control., 2013

A comparative evaluation of stochastic-based inference methods for Gaussian process models.
Mach. Learn., 2013

Exact-Approximate Bayesian Inference for Gaussian Processes.
CoRR, 2013

ODE parameter inference using adaptive gradient matching with Gaussian processes.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Towards Causal Modeling of Human Behavior.
Proceedings of the Neural Nets and Surroundings - 22nd Italian Workshop on Neural Nets, 2012

From speech to personality: mapping voice quality and intonation into personality differences.
Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29, 2012

Predicting the conflict level in television political debates: an approach based on crowdsourcing, nonverbal communication and gaussian processes.
Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29, 2012

2011
A Perturbative Approach to Novelty Detection in Autoregressive Models.
IEEE Trans. Signal Process., 2011

Simulated annealing for supervised gene selection.
Soft Comput., 2011

Discussion of the paper: "Sampling schemes for generalized linear Dirichlet process random effects models" by M. Kyung, J. Gill, and G. Casella.
Stat. Methods Appl., 2011

Approximate inference of the bandwidth in multivariate kernel density estimation.
Comput. Stat. Data Anal., 2011

2010
Applying the Possibilistic c-Means Algorithm in Kernel-Induced Spaces.
IEEE Trans. Fuzzy Syst., 2010

Information theoretic novelty detection.
Pattern Recognit., 2010

2009
A comparative evaluation of nonlinear dynamics methods for time series prediction.
Neural Comput. Appl., 2009

Soft ranking in clustering.
Neurocomputing, 2009

Clustering in the membership embedding space.
Int. J. Knowl. Eng. Soft Data Paradigms, 2009

Dealing with non-metric dissimilarities in fuzzy central clustering algorithms.
Int. J. Approx. Reason., 2009

The discriminating power of random features.
Proceedings of the Neural Nets WIRN09, 2009

2008
A survey of kernel and spectral methods for clustering.
Pattern Recognit., 2008

An Experimental Comparison of Kernel Clustering Methods.
Proceedings of the New Directions in Neural Networks, 2008

Detecting Suspicious Behavior in Surveillance Images.
Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Stability and Performances in Biclustering Algorithms.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2008

2007
Possibilistic Clustering in Feature Space.
Proceedings of the Applications of Fuzzy Sets Theory, 2007

Membership Embedding Space Approach and Spectral Clustering.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007

SVM-Based Time Series Prediction with Nonlinear Dynamics Methods.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007

Local Learning of Tide Level Time Series using a Fuzzy Approach.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Supervised Classification and Gene Selection Using Simulated Annealing.
Proceedings of the International Joint Conference on Neural Networks, 2006

Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis.
Proceedings of the Computational Methods in Systems Biology, International Conference, 2006

2005
Soft Rank Clustering.
Proceedings of the Neural Nets, 16th Italian Workshop on Neural Nets, 2005

Unsupervised Gene Selection and Clustering Using Simulated Annealing.
Proceedings of the Fuzzy Logic and Applications, 6th International Workshop, 2005

2004
ERAF: A R Package for Regression and Forecasting.
Proceedings of the Biological and Artificial Intelligence Environments, 2004


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