Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleJanuary 2022
Adversarial robustness guarantees for Gaussian processes
The Journal of Machine Learning Research (JMLR), Volume 23, Issue 1Article No.: 146, Pages 6524–6578Gaussian processes (GPs) enable principled computation of model uncertainty, making them attractive for safety-critical applications. Such scenarios demand that GP decisions are not only accurate, but also robust to perturbations. In this paper we present ...
- abstractOctober 2021
Integrated scientific modeling and lab automation (keynote)
SPLASH Companion 2021: Companion Proceedings of the 2021 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for HumanityPage 1https://doi.org/10.1145/3484271.3490527The cycle of observation, hypothesis formulation, experimentation, and falsification that has driven scientific and technical progress is lately becoming automated in all its separate components. However, integration between these automated components ...
- ArticleAugust 2021
Lumpability for Uncertain Continuous-Time Markov Chains
AbstractThe assumption of perfect knowledge of rate parameters in continuous-time Markov chains (CTMCs) is undermined when confronted with reality, where they may be uncertain due to lack of information or because of measurement noise. In this paper we ...
- research-articleDecember 2020
Safety Guarantees for Iterative Predictions with Gaussian Processes
- Kyriakos Polymenakos,
- Luca Laurenti,
- Andrea Patane,
- Jan-Peter Calliess,
- Luca Cardelli,
- Marta Kwiatkowska,
- Alessandro Abate,
- Stephen Roberts
2020 59th IEEE Conference on Decision and Control (CDC)Pages 3187–3193https://doi.org/10.1109/CDC42340.2020.9304029Gaussian Processes (GPs) are widely employed in control and learning because of their principled treatment of uncertainty. However, tracking uncertainty for iterative, multi-step predictions in general leads to an analytically intractable problem. While ...
- ArticleSeptember 2020
Kaemika App: Integrating Protocols and Chemical Simulation: Integrating Protocols and Chemical Simulation
AbstractKaemika is an app available on the four major app stores. It provides deterministic and stochastic simulation, supporting natural chemical notation enhanced with recursive and conditional generation of chemical reaction networks. It has a liquid-...
-
- research-articleDecember 2019
PID Control of Biochemical Reaction Networks
2019 IEEE 58th Conference on Decision and Control (CDC)Pages 8372–8379https://doi.org/10.1109/CDC40024.2019.9029172Principles of feedback control have been shown to naturally arise in biological systems and successfully applied to build synthetic circuits. In this work we consider Biochemical Reaction Networks (CRNs) as a paradigm for modelling biochemical systems and ...
- research-articleJuly 2019
Symbolic computation of differential equivalences
Theoretical Computer Science (TCSC), Volume 777, Issue CPages 132–154https://doi.org/10.1016/j.tcs.2019.03.018AbstractOrdinary differential equations (ODEs) are widespread in many natural sciences including chemistry, ecology, and systems biology, and in disciplines such as control theory and electrical engineering. Building on the celebrated ...
- research-articleJuly 2019
Central Limit Model Checking
ACM Transactions on Computational Logic (TOCL), Volume 20, Issue 4Article No.: 19, Pages 1–35https://doi.org/10.1145/3331452We consider probabilistic model checking for continuous-time Markov chains (CTMCs) induced from Stochastic Reaction Networks against a fragment of Continuous Stochastic Logic (CSL) extended with reward operators. Classical numerical algorithms for CSL ...
- research-articleApril 2019
Comparing chemical reaction networks: A categorical and algorithmic perspective
Theoretical Computer Science (TCSC), Volume 765, Issue CPages 47–66https://doi.org/10.1016/j.tcs.2017.12.018AbstractWe study chemical reaction networks (CRNs) as a kernel model of concurrency provided with semantics based on ordinary differential equations. We investigate the problem of comparing two CRNs, i.e., to decide whether the solutions of a ...
- research-articleApril 2019
Efficiency through uncertainty: scalable formal synthesis for stochastic hybrid systems
HSCC '19: Proceedings of the 22nd ACM International Conference on Hybrid Systems: Computation and ControlPages 240–251https://doi.org/10.1145/3302504.3311805This work targets the development of an efficient abstraction method for formal analysis and control synthesis of discrete-time stochastic hybrid systems (SHS) with linear dynamics. The focus is on temporal logic specifications over both finite- and ...
- research-articleJanuary 2019
Robustness guarantees for Bayesian inference with Gaussian processes
AAAI'19/IAAI'19/EAAI'19: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial IntelligenceArticle No.: 952, Pages 7759–7768https://doi.org/10.1609/aaai.v33i01.33017759Bayesian inference and Gaussian processes are widely used in applications ranging from robotics and control to biological systems. Many of these applications are safety-critical and require a characterization of the uncertainty associated with the ...
- articleDecember 2018
Computing with biological switches and clocks
- Neil Dalchau,
- Gregory Szép,
- Rosa Hernansaiz-Ballesteros,
- Chris P. Barnes,
- Luca Cardelli,
- Andrew Phillips,
- Attila Csikász-Nagy
Natural Computing: an international journal (NATC), Volume 17, Issue 4Pages 761–779https://doi.org/10.1007/s11047-018-9686-xThe complex dynamics of biological systems is primarily driven by molecular interactions that underpin the regulatory networks of cells. These networks typically contain positive and negative feedback loops, which are responsible for switch-like and ...
- articleMarch 2018
Programming discrete distributions with chemical reaction networks
Natural Computing: an international journal (NATC), Volume 17, Issue 1Pages 131–145https://doi.org/10.1007/s11047-017-9667-5We explore the range of probabilistic behaviours that can be engineered with Chemical Reaction Networks (CRNs). We give methods to "program" CRNs so that their steady state is chosen from some desired target distribution that has finite support in $${\...
- articleMarch 2018
Chemical reaction network designs for asynchronous logic circuits
Natural Computing: an international journal (NATC), Volume 17, Issue 1Pages 109–130https://doi.org/10.1007/s11047-017-9665-7Chemical reaction networks (CRNs) are a versatile language for describing the dynamical behaviour of chemical kinetics, capable of modelling a variety of digital and analogue processes. While CRN designs for synchronous sequential logic circuits have ...
- ArticleApril 2017
ERODE: A Tool for the Evaluation and Reduction of Ordinary Differential Equations
Proceedings, Part II, of the 23rd International Conference on Tools and Algorithms for the Construction and Analysis of Systems - Volume 10206Pages 310–328https://doi.org/10.1007/978-3-662-54580-5_19We present ERODE, a multi-platform tool for the solution and exact reduction of systems of ordinary differential equations ODEs. ERODE supports two recently introduced, complementary, equivalence relations over ODE variables: forward differential ...
- research-articleApril 2017
Reachability Computation for Switching Diffusions: Finite Abstractions with Certifiable and Tuneable Precision
HSCC '17: Proceedings of the 20th International Conference on Hybrid Systems: Computation and ControlPages 55–64https://doi.org/10.1145/3049797.3049812We consider continuous time stochastic hybrid systems with no resets and continuous dynamics described by linear stochastic differential equations -- models also known as switching diffusions. We show that for this class of models reachability (and ...
- research-articleJuly 2016
Comparing Chemical Reaction Networks: A Categorical and Algorithmic Perspective
LICS '16: Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer SciencePages 485–494https://doi.org/10.1145/2933575.2935318We study chemical reaction networks (CRNs) as a kernel language for concurrency models with semantics based on ordinary differential equations. We investigate the problem of comparing two CRNs, i.e., to decide whether the trajectories of a source CRN can ...
- ArticleApril 2016
Efficient Syntax-Driven Lumping of Differential Equations
Proceedings of the 22nd International Conference on Tools and Algorithms for the Construction and Analysis of Systems - Volume 9636Pages 93–111https://doi.org/10.1007/978-3-662-49674-9_6We present an algorithm to compute exact aggregations of a class of systems of ordinary differential equations ODEs. Our approach consists in an extension of Paige and Tarjan's seminal solution to the coarsest refinement problem by encoding an ODE ...
- research-articleJanuary 2016
Symbolic computation of differential equivalences
POPL '16: Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming LanguagesPages 137–150https://doi.org/10.1145/2837614.2837649Ordinary differential equations (ODEs) are widespread in many natural sciences including chemistry, ecology, and systems biology, and in disciplines such as control theory and electrical engineering. Building on the celebrated molecules-as-processes ...
Also Published in:
ACM SIGPLAN Notices: Volume 51 Issue 1 - ArticleAugust 2015
Automated Design and Verification of Localized DNA Computation Circuits
DNA 21: Proceedings of the 21st International Conference on DNA Computing and Molecular Programming - Volume 9211Pages 168–180https://doi.org/10.1007/978-3-319-21999-8_11Simple computations can be performed using the interactions between single-stranded molecules of DNA. These interactions are typically toehold-mediated strand displacement reactions in a well-mixed solution. We demonstrate that a DNA circuit with ...