23 papers · ranked by Valyu relevance
Roman Linne, Jannis Hildebrandt, Gerd Bohner, Hans-Peter Erb
We present a theory of sequential information processing in persuasion (SIP). It extends assumptions of the heuristic-systematic model, in particular the idea that information encountered early in a persuasion situation may affect the processing of subsequent information. SIP also builds on the abstraction from…
Theresa H. McKim, Theresa M. Desrochers
Many fundamental human behaviors contain multiple sequences performed to reach a desired outcome, such as cooking. Reward is inherently associated with sequence completion and has been shown to generally enhance cognitive control. However, the impact of reward on cognitive sequence processing remains unexplored. To…
Amin Nazerzadeh, Medha Porwal, J. Andrew Pruszynski, Jörn Diedrichsen
Sequential movements rely on two information sources: external sensory cues and internal memory representations. Although often both sources jointly drive sequential behavior, previous research has primarily examined them in isolation. To address this, we trained participants to perform sequences of rapid finger…
Kevin Zhang, Neha Patki, Kalyan Veeramachaneni
The goal of this paper is to describe a system for generating synthetic sequential data within the Synthetic data vault. To achieve this, we present the Sequential model currently in SDV, an end-to-end framework that builds a generative model for multi-sequence, real-world data. This includes a novel neural…
Mehrdad Kashefi, Sasha Reschechtko, Giacomo Ariani, Mahdiyar Shahbazi + 3 more
Real world actions often comprise of a series of movements that cannot be entirely planned before initiation. When these actions are executed rapidly, the planning of multiple future movements needs to occur simultaneously with the ongoing action. How the brain solves this task remains unknown. Here we address this…
Willem B. Verwey
An exhaustive review is reported of over 25 years of research with the Discrete Sequence Production (DSP) task as reported in well over 100 articles. In line with the increasing call for theory development, this culminates into proposing the second version of the Cognitive framework of Sequential Motor Behavior (C-SMB…
Andrew D Levy, Peter Zeidman, Karl Friston
Sequential experimental paradigms are fundamental to cognitive neuroscience, yet standard event-related response analysis struggles with the temporal variability inherent to these designs. Conventional epoching treats each event within a sequence as an independent response, discarding the temporal dependencies between…
Anne Voormann, Jeff Miller
A common finding across numerous response time (RT) paradigms is that the mean RT in one trial depends strongly on the characteristics of the immediately preceding trial. Although such sequential effects have usually only been considered within each single paradigm in isolation from the others, there are important…
Jan Niklas Adams, Gyunam Park, Sergej Levich, Daniel Schuster + 1 more
'Wil M. P. van der Aalst'] Abstract. Traditional process mining techniques take event data as input where each event is associated with exactly one object. An object represents the instantiation of a process. Object-centric event data contain events associated with multiple objects expressing the interaction of…
R. Hamel, B. M. Waltzing, M.R. Hinder, C. McAllister + 2 more
Motor sequence learning gradually quickens reaction time, suggesting that sequence learning alters motor preparation processes. Interestingly, evidence has shown that preparing sequence movements decreases short intracortical inhibition (SICI) in the contralateral motor cortex (M1), but also that sequence learning…
Qi Zhang, Chang Liu, Stephen Wu, Ryo Yoshida
In the last few years, de novo molecular design using machine learning has made great technical progress but its practical deployment has not been as successful. This is mostly owing to the cost and technical difficulty of synthesizing such computationally designed molecules. To overcome such barriers, various methods…
Anna Kalenkova, Lewis Mitchell, Matthew Roughan
Process mining is a well-established discipline of data analysis focused on the discovery of process models from information systems' event logs. Recently, an emerging subarea of process mining – stochastic process discovery has started to evolve. Stochastic process discovery considers frequencies of events in the…
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…
Bernard Costa, Marcus V. C. Baldo, Carolina Feher da Silva
Adaptive human behaviour depends on the ability to detect regularities and probabilistic structures within a noisy environment. Repeated binary choice tasks, in which individuals predict one of two possible outcomes, have long served as a fundamental tool for investigating learning, reward processing, and…
Erik Skau, Andrew Hollis, Stephan Eidenbenz, Kim J.R. Rasmussen + 1 more
'Boian S. Alexandrov'] Monitoring of industrial processes is a critical capability in industry and in government to ensure reliability of production cycles, quick emergency response, and national security. Process monitoring allows users to gauge the progress of an organization in an industrial process or predict the…
Manuél Camargo, Daniel Barón, Marlon Dumas, Oscar González-Rojas
Business process simulation is a well-known approach to estimate the impact of changes to a process with respect to time and cost measures – a practice known as what-if process analysis. The usefulness of such estimations hinges on the accuracy of the underlying simulation model. Data-Driven Simulation (DDS) methods…
Authors not listed
Sequence is the critical determinant of macromolecular function, yet current polymer design approaches often optimize monomer composition and ratios while ignoring sequence. This creates poorly defined design spaces for active learning that miss the vast combinatorial landscape of sequence possibilities. We introduce…
Bianka Bakullari, Wil M. P. van der Aalst
—Process mining methods often analyze processes in terms of the individual end-to-end process runs. Process behavior, however, may materialize as a general state of many involved process components, which can not be captured by looking at the individual process instances. A more holistic state of the process can be…
Daniel Ortiz-Martínez
Background Bioinformatics data analysis faces significant challenges. As data analysis often takes the form of pipelines or workflows, workflow managers (WfMs) have become essential. Data flow programming constitutes the preferred approach in WfMs, enabling parallel processes activated reactively based on input…
Authors not listed
The lithium-ion batteries (LIBs) industry has expanded quickly despite technological constraints. Additionally, raw materials supply, end-of-life (EoL) management, and the creation of LIB manufacturing policies are receiving attention. All these concerns could be addressed simultaneously by integrating recycling of EoL…
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…
James P. Crutchfield, Antonio M. Scarfone
We show that mixtures comprising multicomponent systems typically are much more structurally complex than the sum of their parts; sometimes, infinitely more complex. We contrast this with the more familiar notion of statistical mixtures, demonstrating how statistical mixtures miss key aspects of emergent hierarchical…
Josh M. Salet, Wouter Kruijne, Hedderik van Rijn, Eckart Zimmermann + 1 more
Timing studies on statistical learning predominantly present temporal regularities in a discrete, trial-by-trial manner. This, however, is a simplified representation of nature’s complex temporal structure in which regularities are embedded in a continuous stream of interrupting, irregular events. Recent studies using…