Guido Sanguinetti

Publication Activity (10 Years)

Years Active: 2005-2023
Publications (10 Years): 50

Top Topics

Gaussian Process

Gradient Ascent

Top Venues

Publications

Viplove Arora, Daniele Irto, Sebastian Goldt, Guido Sanguinetti
Quantifying lottery tickets under label noise: accuracy, calibration, and complexity. CoRR (2023)
Viplove Arora, Daniele Irto, Sebastian Goldt, Guido Sanguinetti
Quantifying lottery tickets under label noise: accuracy, calibration, and complexity. UAI (2023)
Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti
Attacks on Online Learners: a Teacher-Student Analysis. CoRR (2023)
Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti
Attacks on Online Learners: a Teacher-Student Analysis. NeurIPS (2023)
Ginevra Carbone, Luca Bortolussi, Guido Sanguinetti
Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks. IJCNN (2022)
Svitlana Braichenko, Ramon Grima, Guido Sanguinetti
Bayesian Learning of Effective Chemical Master Equations in Crowded Intracellular Conditions. CMSB (2022)
Luca Bortolussi, Ginevra Carbone, Luca Laurenti, Andrea Patane, Guido Sanguinetti, Matthew Wicker
On the Robustness of Bayesian Neural Networks to Adversarial Attacks. CoRR (2022)
Christos Maniatis, Catalina A. Vallejos, Guido Sanguinetti
SCRaPL: A Bayesian hierarchical framework for detecting technical associates in single cell multiomics data. PLoS Comput. Biol. 18 (6) (2022)
Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks. CoRR (2021)
Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
Random Projections for Improved Adversarial Robustness. IJCNN (2021)
Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
Random Projections for Improved Adversarial Robustness. CoRR (2021)
Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patane, Luca Bortolussi, Guido Sanguinetti
Robustness of Bayesian Neural Networks to Gradient-Based Attacks. CoRR (2020)
Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patané, Luca Bortolussi, Guido Sanguinetti
Robustness of Bayesian Neural Networks to Gradient-Based Attacks. NeurIPS (2020)
Giulio Caravagna, Guido Sanguinetti, Trevor A. Graham, Andrea Sottoriva
The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data. BMC Bioinform. 21 (1) (2020)
Michalis Michaelides, Jane Hillston, Guido Sanguinetti
Statistical Abstraction for Multi-scale Spatio-temporal Systems. ACM Trans. Model. Comput. Simul. 29 (4) (2019)
Kaan Öcal, Ramon Grima, Guido Sanguinetti
Wasserstein Distances for Estimating Parameters in Stochastic Reaction Networks. CMSB (2019)
Michalis Michaelides, Jane Hillston, Guido Sanguinetti
Geometric fluid approximation for general continuous-time Markov chains. CoRR (2019)
Ankit Gupta, Mustafa Khammash, Guido Sanguinetti
Bayesian Parameter Estimation for Stochastic Reaction Networks from Steady-State Observations. CMSB (2019)
Michael Everett Rule, David Schnoerr, Matthias H. Hennig, Guido Sanguinetti
Neural field models for latent state inference: Application to large-scale neuronal recordings. PLoS Comput. Biol. 15 (11) (2019)
Guido Sanguinetti, David Safránek
Preface. SASB 335 (2018)
Luca Bortolussi, Guido Sanguinetti
Intrinsic Geometric Vulnerability of High-Dimensional Artificial Intelligence. CoRR (2018)
Michael Everett Rule, Guido Sanguinetti
Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations. Neural Comput. 30 (10) (2018)
Chantriolnt-Andreas Kapourani, Guido Sanguinetti
BPRMeth: a flexible Bioconductor package for modelling methylation profiles. Bioinform. 34 (14) (2018)
Luca Bortolussi, Guido Sanguinetti, Simone Silvetti
Bayesian Statistical parametric Verification and synthesis by Machine Learning. WSC (2018)
Dimitrios Milios, Guido Sanguinetti, David Schnoerr
Probabilistic Model Checking for Continuous-Time Markov Chains via Sequential Bayesian Inference. QEST (2018)
Anastasis Georgoulas, Jane Hillston, Guido Sanguinetti
ProPPA: Probabilistic Programming for Stochastic Dynamical Systems. ACM Trans. Model. Comput. Simul. 28 (1) (2018)
Michalis Michaelides, Jane Hillston, Guido Sanguinetti
Statistical Abstraction for Multi-scale Spatio-Temporal Systems. QEST (2017)
Giulio Caravagna, Daniele Ramazzotti, Guido Sanguinetti
On learning the structure of Bayesian Networks and submodular function maximization. CoRR (2017)
Anastasis Georgoulas, Jane Hillston, Guido Sanguinetti
Unbiased Bayesian inference for population Markov jump processes via random truncations. Stat. Comput. 27 (4) (2017)
Dimitrios Milios, Guido Sanguinetti, David Schnoerr
Probabilistic Model Checking for Continuous Time Markov Chains via Sequential Bayesian Inference. CoRR (2017)
Ezio Bartocci, Luca Bortolussi, Tomás Brázdil, Dimitrios Milios, Guido Sanguinetti
Policy learning in continuous-time Markov decision processes using Gaussian Processes. Perform. Evaluation 116 (2017)
Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
Smoothed model checking for uncertain Continuous-Time Markov Chains. Inf. Comput. 247 (2016)
Michalis Michaelides, Dimitrios Milios, Jane Hillston, Guido Sanguinetti
Property-driven State-Space Coarsening for Continuous Time Markov Chains. CoRR (2016)
Ezio Bartocci, Luca Bortolussi, Tomás Brázdil, Dimitrios Milios, Guido Sanguinetti
Policy Learning for Time-Bounded Reachability in Continuous-Time Markov Decision Processes via Doubly-Stochastic Gradient Ascent. QEST (2016)
Ezio Bartocci, Luca Bortolussi, Tomás Brázdil, Dimitrios Milios, Guido Sanguinetti
Policy learning for time-bounded reachability in Continuous-Time Markov Decision Processes via doubly-stochastic gradient ascent. CoRR (2016)
Chantriolnt-Andreas Kapourani, Guido Sanguinetti
Higher order methylation features for clustering and prediction in epigenomic studies. Bioinform. 32 (17) (2016)
Saulius Lukauskas, Roberto Visintainer, Guido Sanguinetti, Gabriele Beate Schweikert
DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks. BMC Bioinform. 17 (S-16) (2016)
Giulio Caravagna, Luca Bortolussi, Guido Sanguinetti
Matching Models Across Abstraction Levels with Gaussian Processes. CMSB (2016)
Michalis Michaelides, Dimitrios Milios, Jane Hillston, Guido Sanguinetti
Property-Driven State-Space Coarsening for Continuous Time Markov Chains. QEST (2016)
Yuanhua Huang, Guido Sanguinetti
Statistical modeling of isoform splicing dynamics from RNA-seq time series data. Bioinform. 32 (19) (2016)
Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
Machine Learning Methods in Statistical Model Checking and System Design - Tutorial. RV (2015)
Luca Bortolussi, Guido Sanguinetti
Learning and Designing Stochastic Processes from Logical Constraints. Log. Methods Comput. Sci. 11 (2) (2015)
Vân Anh Huynh-Thu, Guido Sanguinetti
Combining tree-based and dynamical systems for the inference of gene regulatory networks. Bioinform. 31 (10) (2015)
Daniel Trejo-Baños, Andrew J. Millar, Guido Sanguinetti
Experimental Design for Inference over the A. thaliana Circadian Clock Network. CMSB (2015)
Ezio Bartocci, Luca Bortolussi, Laura Nenzi, Guido Sanguinetti
System design of stochastic models using robustness of temporal properties. Theor. Comput. Sci. 587 (2015)
Daniel Trejo-Baños, Andrew J. Millar, Guido Sanguinetti
A Bayesian approach for structure learning in oscillating regulatory networks. Bioinform. 31 (22) (2015)
Ezio Bartocci, Luca Bortolussi, Dimitrios Milios, Laura Nenzi, Guido Sanguinetti
Studying Emergent Behaviours in Morphogenesis Using Signal Spatio-Temporal Logic. HSB (2015)
Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
Efficient Stochastic Simulation of Systems with Multiple Time Scales via Statistical Abstraction. CMSB (2015)
Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
U-Check: Model Checking and Parameter Synthesis Under Uncertainty. QEST (2015)
Tom R. Mayo, Gabriele Beate Schweikert, Guido Sanguinetti
D: a kernel-based test for spatially correlated changes in methylation profiles. Bioinform. 31 (6) (2015)
Anastasis Georgoulas, Jane Hillston, Dimitrios Milios, Guido Sanguinetti
Probabilistic Programming Process Algebra. QEST (2014)
Sara Bufo, Ezio Bartocci, Guido Sanguinetti, Massimo Borelli, Umberto Lucangelo, Luca Bortolussi
Temporal Logic Based Monitoring of Assisted Ventilation in Intensive Care Patients. ISoLA (2) (2014)
Ezio Bartocci, Luca Bortolussi, Guido Sanguinetti
Data-Driven Statistical Learning of Temporal Logic Properties. FORMATS (2014)
Luca Bortolussi, Guido Sanguinetti
Smoothed Model Checking for Uncertain Continuous Time Markov Chains. CoRR (2014)
Luca Bortolussi, Guido Sanguinetti
A Statistical Approach for Computing Reachability of Non-linear and Stochastic Dynamical Systems. QEST (2014)
Botond Cseke, Manfred Opper, Guido Sanguinetti
Approximate inference in latent Gaussian-Markov models from continuous time observations. NIPS (2013)
Anastasis Georgoulas, Jane Hillston, Guido Sanguinetti
ABC-Fun: A Probabilistic Programming Language for Biology. CMSB (2013)
Ezio Bartocci, Luca Bortolussi, Guido Sanguinetti
Learning Temporal Logical Properties Discriminating ECG models of Cardiac Arrhytmias. CoRR (2013)
Ezio Bartocci, Luca Bortolussi, Laura Nenzi, Guido Sanguinetti
On the Robustness of Temporal Properties for Stochastic Models. HSB (2013)
Andrea Ocone, Guido Sanguinetti
A stochastic hybrid model of a biological filter. HAS (2013)
Grigorios Skolidis, Guido Sanguinetti
Semisupervised Multitask Learning With Gaussian Processes. IEEE Trans. Neural Networks Learn. Syst. 24 (12) (2013)
Luca Bortolussi, Guido Sanguinetti
Learning and Designing Stochastic Processes from Logical Constraints. QEST (2013)
Andrea Ocone, Andrew J. Millar, Guido Sanguinetti
Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics. Bioinform. 29 (7) (2013)
Andrew Zammit Mangion, Guido Sanguinetti, Visakan Kadirkamanathan
Variational Estimation in Spatiotemporal Systems From Continuous and Point-Process Observations. IEEE Trans. Signal Process. 60 (7) (2012)
Grigorios Skolidis, Guido Sanguinetti
A Case Study on Meta-Generalising: A Gaussian Processes Approach. J. Mach. Learn. Res. 13 (2012)
Grigorios Skolidis, Katja Hansen, Guido Sanguinetti, Matthias Rupp
Multi-task learning for pKa prediction. J. Comput. Aided Mol. Des. 26 (7) (2012)
Anastasis Georgoulas, Allan Clark, Andrea Ocone, Stephen Gilmore, Guido Sanguinetti
A subsystems approach for parameter estimation of ODE models of hybrid systems HSB (2012)
Florian Stimberg, Manfred Opper, Guido Sanguinetti, Andreas Ruttor
Inference in continuous-time change-point models. NIPS (2011)
Maurizio Filippone, Guido Sanguinetti
A Perturbative Approach to Novelty Detection in Autoregressive Models. IEEE Trans. Signal Process. 59 (3) (2011)
Andrea Ocone, Guido Sanguinetti
Reconstructing transcription factor activities in hierarchical transcription network motifs. Bioinform. 27 (20) (2011)
Hafiz Muhammad Shahzad Asif, Guido Sanguinetti
Large-scale learning of combinatorial transcriptional dynamics from gene expression. Bioinform. 27 (9) (2011)
Andrew Zammit Mangion, Ke Yuan, Visakan Kadirkamanathan, Mahesan Niranjan, Guido Sanguinetti
Online Variational Inference for State-Space Models with Point-Process Observations. Neural Comput. 23 (8) (2011)
Grigorios Skolidis, Guido Sanguinetti
Bayesian Multitask Classification With Gaussian Process Priors. IEEE Trans. Neural Networks 22 (12) (2011)
Maurizio Filippone, Guido Sanguinetti
Approximate inference of the bandwidth in multivariate kernel density estimation. Comput. Stat. Data Anal. 55 (12) (2011)
Michael Dewar, Visakan Kadirkamanathan, Manfred Opper, Guido Sanguinetti
Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster. BMC Syst. Biol. 4 (2010)
Manfred Opper, Andreas Ruttor, Guido Sanguinetti
Approximate inference in continuous time Gaussian-Jump processes. NIPS (2010)
Hafiz Muhammad Shahzad Asif, Matthew D. Rolfe, Jeffrey Green, Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti
TFInfer: a tool for probabilistic inference of transcription factor activities. Bioinform. 26 (20) (2010)
Manfred Opper, Guido Sanguinetti
Learning combinatorial transcriptional dynamics from gene expression data. Bioinform. 26 (13) (2010)
Maurizio Filippone, Guido Sanguinetti
Information theoretic novelty detection. Pattern Recognit. 43 (3) (2010)
Guido Sanguinetti, Andreas Ruttor, Manfred Opper, Cédric Archambeau
Switching regulatory models of cellular stress response. Bioinform. 25 (10) (2009)
Richard D. Pearson, Xuejun Liu, Guido Sanguinetti, Marta Milo, Neil D. Lawrence, Magnus Rattray
puma: a Bioconductor package for propagating uncertainty in microarray analysis. BMC Bioinform. 10 (2009)
Josselin Noirel, Guido Sanguinetti, Phillip C. Wright
Identifying differentially expressed subnetworks with MMG. Bioinform. 24 (23) (2008)
Guido Sanguinetti, Josselin Noirel, Phillip C. Wright
MMG: a probabilistic tool to identify submodules of metabolic pathways. Bioinform. 24 (8) (2008)
Guido Sanguinetti
Dimensionality Reduction of Clustered Data Sets. IEEE Trans. Pattern Anal. Mach. Intell. 30 (3) (2008)
Manfred Opper, Guido Sanguinetti
Variational inference for Markov jump processes. NIPS (2007)
Neil D. Lawrence, Guido Sanguinetti, Magnus Rattray
Modelling transcriptional regulation using Gaussian Processes. NIPS (2006)
Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence
Identifying Submodules of Cellular Regulatory Networks. CMSB (2006)
Guido Sanguinetti, Neil D. Lawrence, Magnus Rattray
Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities. Bioinform. 22 (22) (2006)
Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence
A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription. Bioinform. 22 (14) (2006)
Magnus Rattray, Xuejun Liu, Guido Sanguinetti, Marta Milo, Neil D. Lawrence
Propagating uncertainty in microarray data analysis. Briefings Bioinform. 7 (1) (2006)
Guido Sanguinetti, Neil D. Lawrence
Missing Data in Kernel PCA. ECML (2006)
Guido Sanguinetti, Marta Milo, Magnus Rattray, Neil D. Lawrence
Accounting for probe-level noise in principal component analysis of microarray data. Bioinform. 21 (19) (2005)