22 papers · ranked by Valyu relevance
Diogo Pacheco, Marcos Oliveira, Zexun Chen, Hugo Barbosa + 3 more
'Brooke Foucault Welles' 'Gourab Ghoshal' 'Ronaldo Menezes'] Human travelling behaviours are markedly regular, to a large extent, predictable, and mostly driven by biological necessities (e.g. sleeping, eating) and social constructs (e.g. school schedules, synchronisation of labour). Not surprisingly, such…
Neomi Singer, Nori Jacoby, Talma Hendler, Roni Granot
Music is a complex phenomenon that elicits a range of emotional responses, influenced by numerous variables, such as rhythm, melody and harmony. One interesting aspect of music is listeners’ ability to predict its continuation as it unfolds - an inherent attribute hypothesized to contribute to our emotional response to…
Yiyuan Teresa Huang, Zenas C. Chao
Our brain uses prior experience to anticipate the timing of upcoming events. This dynamical process can be modeled using a hazard function derived from the probability distribution of event timings. However, the contexts of an event can lead to various probability distributions for the same event, and it remains…
Joseph Sollini, Katarina C. Poole, Dominic Blauth-Muszkowski, Jennifer K. Bizley
'Jennifer K. Bizley'] The cochlea decomposes sounds into separate frequency channels, from which the auditory brain must reconstruct the auditory scene. To do this the auditory system must make decisions about which frequency information should be grouped together, and which should remain distinct. Two key cues for…
Camila Silveira Agostino, Herman Hinrichs, Toemme Noesselt
Predicting future events is a fundamental cognitive ability which often depends on the volatility of the environment. Previous studies on apparent motion reported that when the brain is confronted with low levels of predictability, activity in low-level sensory areas is increased, including primary visual cortex.…
Chenyu Dong, Davide Faranda, Adriano Gualandi, Valerio Lucarini + 1 more
'Gianmarco Mengaldo'] Title: Significance In many complex systems, predictability can be substantially state-dependent. We propose here a purely data-driven approach for estimating the local predictability at different time scales. The effectiveness of our approach is validated against existing knowledge, and its…
Yi Gao, Irene Echeverria-Altuna, Sage E.P Boettcher, Anna C Nobre
The goal-dependent use of temporal expectations enhances visual performance, even without concurrent spatial or motor predictions, yet the underlying neural mechanisms remain unclear. To identify the stages of stimulus processing influenced by temporal orienting of attention, we recorded EEG while participants…
Johannes Wetekam, Chloé Dumeige, Manon Beurtey, Sophie Herbst
Knowing when and what sounds will occur makes auditory perception more efficient. Yet the mechanisms by which these predictive dimensions jointly shape perception remain unclear, particularly under uncertain listening conditions. Here, we tested the effects of temporal and spectral predictability in a challenging…
Gal Vishne, Leon Y. Deouell, Ayelet N. Landau
To interact effectively with our surroundings, we rely on strategies to reduce uncertainty. One important source of information is temporal regularities, which enable us to form predictions about when events will occur, and through this, prepare for them in advance. Such preparation was shown to facilitate motor…
En Xu, Yilin Bi, Hsun‐Ming Hu, Xin Chen + 4 more
a Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China b CompleX Lab, University of Electronic Science and Technology of China, Chengdu, 611731, China c Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, 518055, China d School of Computer…
Drew Cappotto, Dan Luo, Hiu Wai Lai, Fei Peng + 3 more
'Jan Wilbert Hendrik Schnupp' 'Ryszard Auksztulewicz'] Introduction Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli and their timing, both of which are known to interactively modulate sensory…
Aysun Duyar, Shiyang Ren, Marisa Carrasco
Temporal attention is voluntarily deployed at specific moments, whereas temporal expectation is deployed according to timing probabilities. When the target appears at an expected moment in a sequence, temporal attention improves performance at the attended moments, but the timing and the precision of the attentional…
Sahand Karimi-Arpanahi, S. Ali Pourmousavi, Nariman Mahdavi
Title: Summary Decision-making in the power systems domain often relies on predictions of renewable generation. While sophisticated forecasting methods have been developed to improve the accuracy of such predictions, their accuracy is limited by the inherent predictability of the data used. However, the predictability…
Alexandra Bezbochina, Elizaveta Stavinova, Anton Kovantsev, Petr Chunaev + 1 more
'Petr Chunaev' 'Mohammad Reza Rahimi Tabar'] Driven by the variety of available measures intended to estimate predictability of diverse objects such as time series and network links, this paper presents a comprehensive overview of the existing literature in this domain. Our overview delves into predictability from two…
Samuel Genheden, Agnes Mårdh, Gustav Lahti, Ola Engkvist + 2 more
We present machine learning models for predicting the chemical context for Buchwald-Hartwig coupling reactions. Using reaction data from in-house electronic lab notebooks, we train two models: one based on single-label data and one based on multi-label data. Both models show excellent top-3 accuracy around 90%, which…
Jiancang Zhuang, Didier Sornette
Earthquakes resist deterministic prediction, yet their occurrence is not fully random. This paper develops a unified information-theoretic framework to quantify predictability. By reviewing Shannon entropy and the Kullback-Leibler divergence, we formalize predictability as the entropy gap between complete randomness…
Egor Surkov, Dmitry Osin, Evgeny Burnaev, Egor Shvetsov
This paper studies forecasting of the future distribution of events in human action sequences, a task essential in domains like retail, finance, healthcare, and recommendation systems where the precise temporal order is often less critical than the set of outcomes. We challenge the dominant autoregressive paradigm and…
Authors not listed
Kinetic modeling is essential for predicting changes in food quality during processing and storage. This study evaluates the application of physics-informed neural networks (PINN) for food kinetic modeling, integrating kinetic insights into neural network frameworks. Based on three case studies, namely seed drying…
Authors not listed
Accurate prediction of chemical reaction yields remains essential for accelerating synthesis optimization, yet current machine learning models face critical limitations in capturing temporal dynamics, providing calibrated uncertainty estimates, and explicitly modeling reactant-to-product transformations. Here we…
Authors not listed
A framework for catalysis based on categorical aperture selection rather than temporal acceleration is presented. Traditional catalysis theory describes catalysts as agents that accelerate reactions by lowering activation energies, implicitly treating time as the fundamental variable and reaction rate enhancement as…
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…
Tianfan Jin, Brett M Savoie
Contemporary machine learning algorithms have largely succeeded in automating the development of mathematical models from data. Although this is a striking accomplishment, it leaves unaddressed the multitude of scenarios, especially across the chemical sciences and engineering, where deductive, rather than inductive…