26 papers · ranked by Valyu relevance
Oscar Delaney, Sambhav Maheshwari, Joe O'Brien, Theo Bearman + 1 more
Frontier AI companies first deploy their most advanced models internally, for weeks or months of safety testing, evaluation, and iteration, before a possible public release. For example, Anthropic recently developed a new class of model with advanced cyberoffense-relevant capabilities, Mythos Preview, which was…
Balázs Török, Dávid G. Nagy, Mariann M. Kiss, Karolina Janacsek + 2 more
Internal models capture the regularities of the environment and are central to understanding how humans adapt to environmental statistics. In general, the correct internal model is unknown to observers, instead approximate and transient ones are recruited. However, experimenters assume an ideal observer model, which…
Manuel Baltieri, Martin Biehl, Matteo Capucci, Nathaniel Virgo
—The internal model principle, originally proposed in the theory of control of linear systems, nowadays represents a more general class of results in control theory and cybernetics. The central claim of these results is that, under suitable assumptions, if a system (a controller) can regulate against a class of…
Vadim Weinstein, Tamara Alshammari, Kalle G. Timperi, Mehdi Bennis + 1 more
'Steven M. LaValle'] Abstract. When designing a robot's internal system, one often makes assumptions about the structure of the intended environment of the robot. One may even assign meaning to various internal components of the robot in terms of expected environmental correlates. In this paper we want to make the…
Madhur Mangalam
The concept of internal models dominates contemporary theories of sensorimotor control, with researchers across neurosciences, specifically motor control, routinely explaining observed behaviors through computational representations that supposedly exist within the nervous system. In this perspective, I present a…
Andrew T. Morgan, Lucy S. Petro, Lars Muckli
Human behaviour is dependent on the ability of neuronal circuits to predict the outside world. Neuronal circuits make these predictions based on internal models. Despite our extensive knowledge of the sensory features that drive cortical neurons, we have a limited grasp on the structure of the brain’s internal models.…
Malte Schilling, Katharina Rohlfing, Holk Cruse
What’s next? - To know what comes next is already important in carrying out action and allows us to make fast movements. We use predictions in control of our own movements and to anticipate what is going on around us. Clark’s (in press) perspective is pushing the importance of prediction even further. Predictions are…
Qie Hu, Frauke Oldewurtel, Maximilian Balandat, Evangelos Vrettos + 2 more
'Datong P. Zhou' 'Claire J. Tomlin'] Abstract— The inter-temporal consumption flexibility of commercial buildings can be harnessed to improve the energy efficiency of buildings, or to provide ancillary service to the power grid. To do so, a predictive model of the building's thermal dynamics is required. In this paper…
Michael Goldstein, Ian Vernon, Jonathan A. Cumming
Model or structural discrepancy is an essential component in the analysis of computer simulators, representing the differences between the outputs of the simulator and the real-world system that the simulator seeks to represent. This discrepancy can arise from various sources such as simplifications of the model…
Guus ten Broeke, Hilde Tobi
Complex Adaptive Systems (CAS) is an interdisciplinary and dynamic modelling approach for the study of today’s global challenges. It is used for the explanation, description, and prediction of behaviours of system components and the system at large. To understand and assess the quality of research in which CAS models…
Xiaohan Dou, Chengqi Xue, Gengpei Zhang, Zhihao Jiang + 1 more
In the realm of industrial inspection, the precise assessment of internal thread quality is crucial for ensuring mechanical integrity and safety. However, challenges such as limited internal space, inadequate lighting, and complex geometry significantly hinder high-precision inspection. In this study, we propose an…
Helle W. van den Maagdenberg, Martin Šícho, David Alencar Araripe, Sohvi Luukkonen + 9 more
Building reliable and robust quantitative structure-property relationship (QSPR) models is a challenging task. First, the experimental data needs to be obtained, analyzed and curated. Second, the number of available methods is continuously growing and evaluating different algorithms and methodologies can be arduous.…
Klaus‐Dieter Sommer, P M Harris, Sascha Eichstädt, Roland Füßl + 9 more
'Tanja Dorst' 'Andreas Schütze' 'Michael Heizmann' 'Nadine Schiering' 'Andreas Maier' 'Yuhui Luo' 'Christos Tachtatzis' 'Ivan Andonović' 'Gordon Gourlay'] - 1 Technische Universitaet Ilmenau, Germany - 2 National Physical Laboratory, Teddington, United Kingdom - 3 Physikalisch-Technische Bundesanstalt, Braunschweig and…
Feng Zhu, Yiping Yao, Huilong Chen, Feng Yao
Model reuse is a key issue to be resolved in parallel and distributed simulation at present. However, component models built by different domain experts usually have diversiform interfaces, couple tightly, and bind with simulation platforms closely. As a result, they are difficult to be reused across different…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Fuzhan Rahmanian, Robert M. Lee, Dominik Linzner, Kathrin Michel + 4 more
Predicting and monitoring battery life early and across chemistries is a significant challenge due to the plethora of degradation paths, form factors, and electrochemical testing protocols. Existing models typically translate poorly across different electrode, electrolyte, and additive materials, mostly require a fixed…
Tieu-Long Phan, Hoang-Son Lai Le, Gia-Bao Truong, The-Chuong Trinh + 4 more
HIV-1 (Human immunodeficiency virus-1) has been causing severe pandemics by attacking the immune system of its host. Left untreated, it can lead to AIDS (acquired immunodeficiency syndrome), where death is inevitable due to opportunistic diseases. Therefore, discovering new antiviral drugs against HIV-1 is crucial.…
Roy Abitbol, Eyal Cohen, Mona Kanaan, Bhavna Agrawal + 3 more
'Anuradha Bhamidipaty' 'Erez Bilgory'] Abstract—As artificial intelligence (AI) continues to rapidly advance, there is a growing demand from clients and product managers to integrate AI capabilities into their existing business applications. However, a significant gap exists between the rapid progress in AI and the…
Authors not listed
Finite-temperature lattice free energy differences between polymorphs of molecular crystals are fundamental to understanding and predicting the relative stability relationships underpinning polymorphism, yet are computationally expensive to obtain. Here, we implement and critically assess machine-learning-enabled…
Linda-Sophie Schneider, Patrick Krauß, Nadine Schiering, Christopher Syben + 2 more
Mathematical models are vital to the field of metrology, playing a key role in the derivation of measurement results and the calculation of uncertainties from measurement data, informed by an understanding of the measurement process. These models generally represent the correlation between the quantity being measured…
Niloofar Shahidi, Michael Pan, Soroush Safaei, Kenneth Tran + 2 more
Simulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in…
Michael Pan, Peter J. Gawthrop, Joseph Cursons, Edmund J. Crampin
It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the…
O. Ebenhöh, M. van Aalst, N.P. Saadat, T. Nies + 1 more
The modelbase package is a free expandable Python package for building and analysing dynamic mathematical models of biological systems. Originally it was designed for the simulation of metabolic systems, but it can be used for virtually any deterministic chemical processes. modelbase provides easy construction methods…
Arjen van der Heide
The existing literature on modelling provides two main ways of viewing model migration: a modular view, which seeks to decompose models in their constitutive elements, and thus provides a view on what it is that migrates; and a practice-based view, which focuses on modelling as an activity, and understands a model as…
Yidan Xue, Wahbi K. El-Bouri, Tamás I. Józsa, Stephen J. Payne
Thrombectomy, the mechanical removal of a clot, is the most common way to treat ischaemic stroke with large vessel occlusions. However, perfusion cannot always be restored after such an intervention. It has been hypothesised that the absence of reperfusion is due to the clot fragments that block the downstream vessels.…
Authors not listed
Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture…