Guido Sanguinetti

106 papers A* 2A 1B 3Misc 2Journal 63Unranked 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CoVAE: correlated multimodal generative modeling. CoRR Federico Caretti, Guido Sanguinetti
2026	J	`jnl`	Extending differential gene expression testing to handle genome aneuploidy in cancer. PLoS Comput. Biol. Katsiaryna Davydzenka, Giulio Caravagna, Guido Sanguinetti
2025	J	`jnl`	Balanced Multimodal Learning via Mutual Information. CoRR Rongrong Xie, Guido Sanguinetti
2025	J	`jnl`	Cartan Networks: Group theoretical Hyperbolic Deep Learning. CoRR Federico Milanesio, Matteo Santoro, Pietro Giuseppe Fré, Guido Sanguinetti
2025	J	`jnl`	Information-Theoretic Criteria for Knowledge Distillation in Multimodal Learning. CoRR Rongrong Xie, Yizhou Xu, Guido Sanguinetti
2025	J	`jnl`	Navigation through Non-Compact Symmetric Spaces: a mathematical perspective on Cartan Neural Networks. CoRR Pietro Giuseppe Fré, Federico Milanesio, Guido Sanguinetti, Matteo Santoro
2025	J	`jnl`	On the Robustness of Bayesian Neural Networks to Adversarial Attacks. IEEE Trans. Neural Networks Learn. Syst. Luca Bortolussi, Ginevra Carbone, Luca Laurenti, Andrea Patane, Guido Sanguinetti, Matthew Wicker
2023	A*	`conf`	Attacks on Online Learners: a Teacher-Student Analysis. NeurIPS Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti
2023	J	`jnl`	Attacks on Online Learners: a Teacher-Student Analysis. CoRR Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti
2023	A	`conf`	Quantifying lottery tickets under label noise: accuracy, calibration, and complexity. UAI Viplove Arora, Daniele Irto, Sebastian Goldt, Guido Sanguinetti
2023	J	`jnl`	Quantifying lottery tickets under label noise: accuracy, calibration, and complexity. CoRR Viplove Arora, Daniele Irto, Sebastian Goldt, Guido Sanguinetti
2022	—	`conf`	Bayesian Learning of Effective Chemical Master Equations in Crowded Intracellular Conditions. CMSB Svitlana Braichenko, Ramon Grima, Guido Sanguinetti
2022	J	`jnl`	On the Robustness of Bayesian Neural Networks to Adversarial Attacks. CoRR Luca Bortolussi, Ginevra Carbone, Luca Laurenti, Andrea Patane, Guido Sanguinetti, Matthew Wicker
2022	B	`conf`	Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks. IJCNN Ginevra Carbone, Luca Bortolussi, Guido Sanguinetti
2022	J	`jnl`	SCRaPL: A Bayesian hierarchical framework for detecting technical associates in single cell multiomics data. PLoS Comput. Biol. Christos Maniatis, Catalina A. Vallejos, Guido Sanguinetti
2021	B	`conf`	Random Projections for Improved Adversarial Robustness. IJCNN Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
2021	J	`jnl`	Random Projections for Improved Adversarial Robustness. CoRR Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
2021	J	`jnl`	Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks. CoRR Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
2020	—	`ed.`	Proceedings of SASB 2018, the 7th International Workshop on Static Analysis and Systems Biology, University of Edinburgh, September 7, 2016 SASB Guido Sanguinetti, David Safránek
2020	A*	`conf`	Robustness of Bayesian Neural Networks to Gradient-Based Attacks. NeurIPS Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patané, Luca Bortolussi, Guido Sanguinetti
2020	J	`jnl`	Robustness of Bayesian Neural Networks to Gradient-Based Attacks. CoRR Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patane, Luca Bortolussi, Guido Sanguinetti
2020	J	`jnl`	The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data. BMC Bioinform. Giulio Caravagna, Guido Sanguinetti, Trevor A. Graham, Andrea Sottoriva
2019	—	`conf`	Bayesian Parameter Estimation for Stochastic Reaction Networks from Steady-State Observations. CMSB Ankit Gupta, Mustafa Khammash, Guido Sanguinetti
2019	—	`ed.`	Computational Methods in Systems Biology - 17th International Conference, CMSB 2019, Trieste, Italy, September 18-20, 2019, Proceedings CMSB Luca Bortolussi, Guido Sanguinetti
2019	J	`jnl`	Geometric fluid approximation for general continuous-time Markov chains. CoRR Michalis Michaelides, Jane Hillston, Guido Sanguinetti
2019	J	`jnl`	Neural field models for latent state inference: Application to large-scale neuronal recordings. PLoS Comput. Biol. Michael Everett Rule, David Schnoerr, Matthias H. Hennig, Guido Sanguinetti
2019	J	`jnl`	Statistical Abstraction for Multi-scale Spatio-temporal Systems. ACM Trans. Model. Comput. Simul. Michalis Michaelides, Jane Hillston, Guido Sanguinetti
2019	—	`conf`	Wasserstein Distances for Estimating Parameters in Stochastic Reaction Networks. CMSB Kaan Öcal, Ramon Grima, Guido Sanguinetti
2018	J	`jnl`	Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations. Neural Comput. Michael Everett Rule, Guido Sanguinetti
2018	J	`jnl`	BPRMeth: a flexible Bioconductor package for modelling methylation profiles. Bioinform. Chantriolnt-Andreas Kapourani, Guido Sanguinetti
2018	Misc	`conf`	Bayesian Statistical parametric Verification and synthesis by Machine Learning. WSC Luca Bortolussi, Guido Sanguinetti, Simone Silvetti
2018	J	`jnl`	Intrinsic Geometric Vulnerability of High-Dimensional Artificial Intelligence. CoRR Luca Bortolussi, Guido Sanguinetti
2018	—	`conf`	Preface. SASB Guido Sanguinetti, David Safránek
2018	J	`jnl`	ProPPA: Probabilistic Programming for Stochastic Dynamical Systems. ACM Trans. Model. Comput. Simul. Anastasis Georgoulas, Jane Hillston, Guido Sanguinetti
2018	—	`conf`	Probabilistic Model Checking for Continuous-Time Markov Chains via Sequential Bayesian Inference. QEST Dimitrios Milios, Guido Sanguinetti, David Schnoerr
2017	J	`jnl`	On learning the structure of Bayesian Networks and submodular function maximization. CoRR Giulio Caravagna, Daniele Ramazzotti, Guido Sanguinetti
2017	J	`jnl`	Policy learning in continuous-time Markov decision processes using Gaussian Processes. Perform. Evaluation Ezio Bartocci, Luca Bortolussi, Tomás Brázdil, Dimitrios Milios, Guido Sanguinetti
2017	J	`jnl`	Probabilistic Model Checking for Continuous Time Markov Chains via Sequential Bayesian Inference. CoRR Dimitrios Milios, Guido Sanguinetti, David Schnoerr
2017	—	`conf`	Statistical Abstraction for Multi-scale Spatio-Temporal Systems. QEST Michalis Michaelides, Jane Hillston, Guido Sanguinetti
2017	J	`jnl`	Unbiased Bayesian inference for population Markov jump processes via random truncations. Stat. Comput. Anastasis Georgoulas, Jane Hillston, Guido Sanguinetti
2016	J	`jnl`	DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks. BMC Bioinform. Saulius Lukauskas, Roberto Visintainer, Guido Sanguinetti, Gabriele Beate Schweikert
2016	J	`jnl`	Higher order methylation features for clustering and prediction in epigenomic studies. Bioinform. Chantriolnt-Andreas Kapourani, Guido Sanguinetti
2016	—	`conf`	Matching Models Across Abstraction Levels with Gaussian Processes. CMSB Giulio Caravagna, Luca Bortolussi, Guido Sanguinetti
2016	—	`conf`	Policy Learning for Time-Bounded Reachability in Continuous-Time Markov Decision Processes via Doubly-Stochastic Gradient Ascent. QEST Ezio Bartocci, Luca Bortolussi, Tomás Brázdil, Dimitrios Milios, Guido Sanguinetti
2016	J	`jnl`	Policy learning for time-bounded reachability in Continuous-Time Markov Decision Processes via doubly-stochastic gradient ascent. CoRR Ezio Bartocci, Luca Bortolussi, Tomás Brázdil, Dimitrios Milios, Guido Sanguinetti
2016	—	`conf`	Property-Driven State-Space Coarsening for Continuous Time Markov Chains. QEST Michalis Michaelides, Dimitrios Milios, Jane Hillston, Guido Sanguinetti
2016	J	`jnl`	Property-driven State-Space Coarsening for Continuous Time Markov Chains. CoRR Michalis Michaelides, Dimitrios Milios, Jane Hillston, Guido Sanguinetti
2016	J	`jnl`	Smoothed model checking for uncertain Continuous-Time Markov Chains. Inf. Comput. Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
2016	J	`jnl`	Statistical modeling of isoform splicing dynamics from RNA-seq time series data. Bioinform. Yuanhua Huang, Guido Sanguinetti
2015	J	`jnl`	A Bayesian approach for structure learning in oscillating regulatory networks. Bioinform. Daniel Trejo-Baños, Andrew J. Millar, Guido Sanguinetti
2015	J	`jnl`	Combining tree-based and dynamical systems for the inference of gene regulatory networks. Bioinform. Vân Anh Huynh-Thu, Guido Sanguinetti
2015	—	`conf`	Efficient Stochastic Simulation of Systems with Multiple Time Scales via Statistical Abstraction. CMSB Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
2015	—	`conf`	Experimental Design for Inference over the A. thaliana Circadian Clock Network. CMSB Daniel Trejo-Baños, Andrew J. Millar, Guido Sanguinetti
2015	J	`jnl`	Learning and Designing Stochastic Processes from Logical Constraints. Log. Methods Comput. Sci. Luca Bortolussi, Guido Sanguinetti
2015	J	`jnl`	M Bioinform. Tom R. Mayo, Gabriele Beate Schweikert, Guido Sanguinetti
2015	B	`conf`	Machine Learning Methods in Statistical Model Checking and System Design - Tutorial. RV Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
2015	—	`conf`	Studying Emergent Behaviours in Morphogenesis Using Signal Spatio-Temporal Logic. HSB Ezio Bartocci, Luca Bortolussi, Dimitrios Milios, Laura Nenzi, Guido Sanguinetti
2015	J	`jnl`	System design of stochastic models using robustness of temporal properties. Theor. Comput. Sci. Ezio Bartocci, Luca Bortolussi, Laura Nenzi, Guido Sanguinetti
2015	—	`conf`	U-Check: Model Checking and Parameter Synthesis Under Uncertainty. QEST Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti
2014	—	`conf`	A Statistical Approach for Computing Reachability of Non-linear and Stochastic Dynamical Systems. QEST Luca Bortolussi, Guido Sanguinetti
2014	—	`conf`	Data-Driven Statistical Learning of Temporal Logic Properties. FORMATS Ezio Bartocci, Luca Bortolussi, Guido Sanguinetti
2014	—	`conf`	Probabilistic Programming Process Algebra. QEST Anastasis Georgoulas, Jane Hillston, Dimitrios Milios, Guido Sanguinetti
2014	J	`jnl`	Smoothed Model Checking for Uncertain Continuous Time Markov Chains. CoRR Luca Bortolussi, Guido Sanguinetti
2014	—	`conf`	Temporal Logic Based Monitoring of Assisted Ventilation in Intensive Care Patients. ISoLA (2) Sara Bufo, Ezio Bartocci, Guido Sanguinetti, Massimo Borelli, Umberto Lucangelo, Luca Bortolussi
2013	—	`conf`	A stochastic hybrid model of a biological filter. HAS Andrea Ocone, Guido Sanguinetti
2013	—	`conf`	ABC-Fun: A Probabilistic Programming Language for Biology. CMSB Anastasis Georgoulas, Jane Hillston, Guido Sanguinetti
2013	—	`conf`	Approximate inference in latent Gaussian-Markov models from continuous time observations. NIPS Botond Cseke, Manfred Opper, Guido Sanguinetti
2013	J	`jnl`	Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics. Bioinform. Andrea Ocone, Andrew J. Millar, Guido Sanguinetti
2013	J	`jnl`	Learning Temporal Logical Properties Discriminating ECG models of Cardiac Arrhytmias. CoRR Ezio Bartocci, Luca Bortolussi, Guido Sanguinetti
2013	—	`conf`	Learning and Designing Stochastic Processes from Logical Constraints. QEST Luca Bortolussi, Guido Sanguinetti
2013	—	`book`	Modeling Conflict Dynamics with Spatio-temporal Data. Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Anaid Flesken, Guido Sanguinetti
2013	—	`conf`	On the Robustness of Temporal Properties for Stochastic Models. HSB Ezio Bartocci, Luca Bortolussi, Laura Nenzi, Guido Sanguinetti
2013	J	`jnl`	Semisupervised Multitask Learning With Gaussian Processes. IEEE Trans. Neural Networks Learn. Syst. Grigorios Skolidis, Guido Sanguinetti
2012	J	`jnl`	A Case Study on Meta-Generalising: A Gaussian Processes Approach. J. Mach. Learn. Res. Grigorios Skolidis, Guido Sanguinetti
2012	—	`conf`	A subsystems approach for parameter estimation of ODE models of hybrid systems HSB Anastasis Georgoulas, Allan Clark, Andrea Ocone, Stephen Gilmore, Guido Sanguinetti
2012	J	`jnl`	Multi-task learning for pKa prediction. J. Comput. Aided Mol. Des. Grigorios Skolidis, Katja Hansen, Guido Sanguinetti, Matthias Rupp
2012	J	`jnl`	Variational Estimation in Spatiotemporal Systems From Continuous and Point-Process Observations. IEEE Trans. Signal Process. Andrew Zammit-Mangion, Guido Sanguinetti, Visakan Kadirkamanathan
2011	J	`jnl`	A Perturbative Approach to Novelty Detection in Autoregressive Models. IEEE Trans. Signal Process. Maurizio Filippone, Guido Sanguinetti
2011	J	`jnl`	Approximate inference of the bandwidth in multivariate kernel density estimation. Comput. Stat. Data Anal. Maurizio Filippone, Guido Sanguinetti
2011	J	`jnl`	Bayesian Multitask Classification With Gaussian Process Priors. IEEE Trans. Neural Networks Grigorios Skolidis, Guido Sanguinetti
2011	—	`conf`	Inference in continuous-time change-point models. NIPS Florian Stimberg, Manfred Opper, Guido Sanguinetti, Andreas Ruttor
2011	J	`jnl`	Large-scale learning of combinatorial transcriptional dynamics from gene expression. Bioinform. Hafiz Muhammad Shahzad Asif, Guido Sanguinetti
2011	J	`jnl`	Online Variational Inference for State-Space Models with Point-Process Observations. Neural Comput. Andrew Zammit-Mangion, Ke Yuan, Visakan Kadirkamanathan, Mahesan Niranjan, Guido Sanguinetti
2011	J	`jnl`	Reconstructing transcription factor activities in hierarchical transcription network motifs. Bioinform. Andrea Ocone, Guido Sanguinetti
2010	—	`ch.`	Approximate Inference for Stochastic Reaction processes. Learning and Inference in Computational Systems Biology Andreas Ruttor, Guido Sanguinetti, Manfred Opper
2010	—	`conf`	Approximate inference in continuous time Gaussian-Jump processes. NIPS Manfred Opper, Andreas Ruttor, Guido Sanguinetti
2010	J	`jnl`	Information theoretic novelty detection. Pattern Recognit. Maurizio Filippone, Guido Sanguinetti
2010	—	`book`	Learning and Inference in Computational Systems Biology. Neil D. Lawrence, Mark A. Girolami, Magnus Rattray, Guido Sanguinetti
2010	J	`jnl`	Learning combinatorial transcriptional dynamics from gene expression data. Bioinform. Manfred Opper, Guido Sanguinetti
2010	J	`jnl`	Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster. BMC Syst. Biol. Michael Dewar, Visakan Kadirkamanathan, Manfred Opper, Guido Sanguinetti
2010	J	`jnl`	TFInfer: a tool for probabilistic inference of transcription factor activities. Bioinform. Hafiz Muhammad Shahzad Asif, Matthew D. Rolfe, Jeffrey Green, Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti
2009	Misc	`conf`	A new probabilistic generative model of parameter inference in biochemical networks. SAC Paola Lecca, Alida Palmisano, Corrado Priami, Guido Sanguinetti
2009	—	`ed.`	Pattern Recognition in Bioinformatics, 4th IAPR International Conference, PRIB 2009, Sheffield, UK, September 7-9, 2009. Proceedings PRIB Visakan Kadirkamanathan, Guido Sanguinetti, Mark A. Girolami, Mahesan Niranjan, Josselin Noirel
2009	J	`jnl`	Switching regulatory models of cellular stress response. Bioinform. Guido Sanguinetti, Andreas Ruttor, Manfred Opper, Cédric Archambeau
2009	J	`jnl`	puma: a Bioconductor package for propagating uncertainty in microarray analysis. BMC Bioinform. Richard D. Pearson, Xuejun Liu, Guido Sanguinetti, Marta Milo, Neil D. Lawrence, Magnus Rattray
2008	J	`jnl`	Dimensionality Reduction of Clustered Data Sets. IEEE Trans. Pattern Anal. Mach. Intell. Guido Sanguinetti
2008	J	`jnl`	Identifying differentially expressed subnetworks with MMG. Bioinform. Josselin Noirel, Guido Sanguinetti, Phillip C. Wright
2008	J	`jnl`	MMG: a probabilistic tool to identify submodules of metabolic pathways. Bioinform. Guido Sanguinetti, Josselin Noirel, Phillip C. Wright
2007	—	`conf`	Variational inference for Markov jump processes. NIPS Manfred Opper, Guido Sanguinetti
2006	J	`jnl`	A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription. Bioinform. Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence
2006	—	`conf`	Identifying Submodules of Cellular Regulatory Networks. CMSB Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence
2006	—	`conf`	Missing Data in Kernel PCA. ECML Guido Sanguinetti, Neil D. Lawrence
2006	—	`conf`	Modelling transcriptional regulation using Gaussian Processes. NIPS Neil D. Lawrence, Guido Sanguinetti, Magnus Rattray
2006	J	`jnl`	Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities. Bioinform. Guido Sanguinetti, Neil D. Lawrence, Magnus Rattray
2006	J	`jnl`	Propagating uncertainty in microarray data analysis. Briefings Bioinform. Magnus Rattray, Xuejun Liu, Guido Sanguinetti, Marta Milo, Neil D. Lawrence
2005	J	`jnl`	Accounting for probe-level noise in principal component analysis of microarray data. Bioinform. Guido Sanguinetti, Marta Milo, Magnus Rattray, Neil D. Lawrence