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Amortized meta-learning methods based on pre-training have propelled fields like natural language processing and vision. Transformer-based neural processes and their variants are leading models for probabilistic meta-learning with a…

Machine Learning · Statistics 2025-03-06 Paul E. Chang , Nasrulloh Loka , Daolang Huang , Ulpu Remes , Samuel Kaski , Luigi Acerbi

Unsupervised machine learning is the training of an artificial intelligence system using information that is neither classified nor labeled, with a view to modeling the underlying structure or distribution in a dataset. Since unsupervised…

Software Engineering · Computer Science 2020-03-18 Xiaoyuan Xie , Zhiyi Zhang , Tsong Yueh Chen , Yang Liu , Pak-Lok Poon , Baowen Xu

We propose a methodology to address two analysis problems concerning complex systems, namely bounding state functionals of stochastic differential equations (SDEs) and verifying set avoidance of systems described by partial differential…

Optimization and Control · Mathematics 2016-03-30 Mohamadreza Ahmadi , Giorgio Valmorbida , Antonis Papachristodoulou

Part II of this paper elaborates on the unique capability of the proposed power flow analysis framework to obtain the true solution corresponding to the stable operating point of a network. It explains the significance of obtaining the true…

Systems and Control · Computer Science 2016-09-06 Sina S. Baghsorkhi , Sergey P. Suetin

Static analysis is the analysis of a program without executing it, usually carried out by an automated tool. Symbolic execution is a popular static analysis technique used both in program verification and in bug detection software. It works…

Software Engineering · Computer Science 2024-08-06 Gabor Horvath , Reka Kovacs , Zoltan Porkolab

The ability to perceive and reason about social interactions in the context of physical environments is core to human social intelligence and human-machine cooperation. However, no prior dataset or benchmark has systematically evaluated…

Artificial Intelligence · Computer Science 2021-03-23 Aviv Netanyahu , Tianmin Shu , Boris Katz , Andrei Barbu , Joshua B. Tenenbaum

Many real-world applications are increasingly incorporating automated decision-making, driven by the widespread adoption of ML/AI inference for planning and guidance. This study examines the growing need for verifiable computing in…

Artificial Intelligence · Computer Science 2025-03-25 Michele Dallachiesa , Antonio Pitasi , David Pinger , Josh Goodbody , Luis Vaello

The characterization of collective behavior and nonequilibrium phase transitions in quantum systems is typically rooted in the analysis of suitable system observables, so-called order parameters. These observables might not be known a…

Quantum Physics · Physics 2026-02-20 Erik Fitzner , Francesco Carnazza , Federico Carollo , Igor Lesanovsky

Model checking is an established technique to formally verify automation systems which are required to be trusted. However, for sufficiently complex systems model checking becomes computationally infeasible. On the other hand, testing,…

Software Engineering · Computer Science 2019-07-30 Igor Buzhinsky , Valeriy Vyatkin

Increasingly demanding performance requirements for dynamical systems motivates the adoption of nonlinear and adaptive control techniques. One challenge is the nonlinearity of the resulting closed-loop system complicates verification that…

Systems and Control · Computer Science 2017-10-03 John F. Quindlen , Ufuk Topcu , Girish Chowdhary , Jonathan P. How

Iterative cycles of theoretical prediction and experimental validation are the cornerstone of the modern scientific method. However, the proverbial "closing of the loop" in experiment-theory cycles in practice are usually ad hoc, often…

The paper documents the implementation of a novel phase-noise analysis module within the open-source QUCS circuit simulator environment. The underlying algorithm is based on a rigorous, unified time-domain methodology of (coupled)…

Systems and Control · Electrical Eng. & Systems 2026-03-10 Torsten Djurhuus , Viktor Krozer

This paper proposes a new class of real-time optimization schemes to overcome system-model mismatch of uncertain processes. This work's novelty lies in integrating derivative-free optimization schemes and multi-fidelity Gaussian processes…

Machine Learning · Computer Science 2021-11-11 Panagiotis Petsagkourakis , Benoit Chachuat , Ehecatl Antonio del Rio-Chanona

This paper introduces a fundamental result, which is relevant for Answer Set programming, and planning. For the first time since the definition of the stable model semantics, the class of logic programs for which a stable model exists is…

Artificial Intelligence · Computer Science 2007-05-23 Stefania Costantini

A great variety of static analyses that compute safety properties of single-thread programs have now been developed. This paper presents a systematic method to extend a class of such static analyses, so that they handle programs with…

Programming Languages · Computer Science 2009-11-02 Jean-Loup Carre , Charles Hymans

Multiphysics simulation frameworks such as MOOSE provide rigorous engines for phase-field materials modeling, yet adoption is constrained by the expertise required to construct valid input files, coordinate parameter sweeps, diagnose…

Artificial Intelligence · Computer Science 2026-03-24 Sukriti Manna , Henry Chan , Subramanian K. R. S. Sankaranarayanan

While the identification of nonlinear dynamical systems is a fundamental building block of model-based reinforcement learning and feedback control, its sample complexity is only understood for systems that either have discrete states and…

Machine Learning · Statistics 2020-06-19 Horia Mania , Michael I. Jordan , Benjamin Recht

Assessment of the degree of boundedness/stability of multidimensional nonlinear systems with time-dependent and nonperiodic coefficients is an important problem in various applied areas which has no adequate resolution yet. Most of the…

Dynamical Systems · Mathematics 2022-06-07 Mark A. Pinsky

We compare the results of two--dimensional simulations to experimental data obtained at Los Alamos National Laboratory in order to validate the FLASH code. FLASH is a multi--physics, block--structured adaptive mesh refinement code for…

Astrophysics · Physics 2007-05-23 Vikram Dwarkadas , Tomek Plewa , Greg Weirs , Chris Tomkins , Mark Marr-Lyon

The catastrophe theory, an effective method for the description of phase transitions, is applied to the Semimicroscopic Algebraic Cluster Model (SACM) as an example of a non-trivial theory. The ground state and excited, rotational phase…

Nuclear Theory · Physics 2017-11-28 E. Lopez-Moreno , P. O. Hess , H. Yepez-Martinez