17 papers · ranked by Valyu relevance
Link R. Swanson
Predictive processing (PP) is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of…
Vighnesh Nagpal, Sarah Blunt, Brendan P. Bowler, Trent J. Dupuy + 2 more
'E. Nielsen' 'Jason Wang'] Orbital eccentricities directly trace the formation mechanisms and dynamical histories of substellar companions. Here, we study the effect of hyperpriors on the population-level eccentricity distributions inferred for the sample of directly imaged substellar companions (brown dwarfs and cold…
Paul Bach, Nadja Klein
Despite their widespread use in practice, the asymptotic properties of Bayesian penalized splines have not been investigated so far. We close this gap and study posterior concentration rates for Bayesian penalized splines in a Gaussian nonparametric regression model. A key feature of the approach is the hyperprior on…
Renato Rodrigues Silva
In the regression analysis, there are situations where the model have more predictor variables than observations of dependent variable, resulting in the problem known as “large p small n”. In the last fifteen years, this problem has been received a lot of attention, specially in the genome-wide context. Here we…
Joseph Melling, William Turner, Hinze Hogendoorn
Visual illusions are systematic misperceptions that can help us glean the heuristics with which the brain constructs visual experience. In a recently discovered visual illusion (the “frame effect”), it has been shown that flashing a stimulus inside of a moving frame produces a large misperception of that stimulus's…
Isaac Overcast, Justin C. Bagley, Michael J. Hickerson
Background Estimating the variability in isolation times across co-distributed taxon pairs that may have experienced the same allopatric isolating mechanism is a core goal of comparative phylogeography. The use of hierarchical Approximate Bayesian Computation (ABC) and coalescent models to infer temporal dynamics of…
Will Newsome
A commentary on Whatever next? Predictive brains, situated agents, and the future of cognitive science by Clark, A. (in press). Behav. Brain Sci. Clark () discusses virtues of the neurocomputational perspective of predictive coding[fn0001], as well as evidential, conceptual, and methodological limits. I expand on some…
Francisco Quiroga, Eric Schulz, Maarten Speekenbrink, Nigel Harvey
Forecasting is an increasingly important part of our daily lives. Many studies on how people produce forecasts frame their behavior as prone to systematic errors. Based on recent evidence on how people learn about functions, we propose that participants’ forecasts are not irrational but rather driven by structured…
H. T. McGovern, Marte Otten
Hierarchical predictive processing provides a framework outlining how prior expectations shape perception and cognition. Here, we highlight hierarchical predictive processing as a framework for explaining how social context and group-based social knowledge can directly shape intergroup perception. More specifically, we…
J. Haarsma, F. Knolle, J.D. Griffin, H. Taverne + 4 more
Alterations in the balance between prior expectations and sensory evidence may account for faulty perceptions and inferences leading to psychosis. However, uncertainties remain about the nature of altered prior expectations and the degree to which they vary with the emergence of psychosis. We explored how expectations…
Tarun Kumar, K Darwin, Srinivasan Parthasarathy, Balaraman Ravindran
Many real-world systems involve higher-order interactions and thus demand complex models such as hypergraphs. For instance, a research article could have multiple collaborating authors, and therefore the co-authorship network is best represented as a hypergraph. In this work, we focus on the problem of hyperedge…
Moayad Alnammi, Shengchao Liu, Spencer S Ericksen, Gene E Ananiev + 6 more
Traditional small molecule drug discovery is a time consuming and costly endeavor. High-throughput chemical screening can only assess a tiny fraction of drug-like chemical space. The strong predictive power of modern machine learning methods for virtual chemical screening enables training models on known active and…
Caroline Bévalot, Florent Meyniel
The brain constantly uses prior knowledge of the statistics of its environment to shape perception. These statistics are often implicit (not directly observable) and gradually learned from observation; but they can also be explicitly communicated to the observer, especially in humans. In value-based decision-making…
Boris Kovalerchuk, Dustin Hayes
—This paper contributes to interpretable machine learning via visual knowledge discovery in parallel coordinates. The concepts of hypercubes and hyper-blocks are used as easily understandable by end-users in the visual form in parallel coordinates. The Hyper algorithm for classification with mixed and pure hyper-blocks…
Cécile Gal, Ioana Țincaș, Vasile V. Moca, Andrei Ciuparu + 4 more
Recognising objects is a vital skill on which humans heavily rely to respond quickly and adaptively to their environment. Yet, we lack understanding on the role visual information sampling plays in this process, and its relation to the individual’s priors. To bridge this gap, the eye-movements of 18 adult participants…
Tony Gracious, Ambedkar Dukkipati
The explosion of digital information and the growing involvement of people in social networks led to enormous research activity to develop methods that can extract meaningful information from interaction data. Commonly, interactions are represented by edges in a network or a graph, which implicitly assumes that the…
Riley Hickman, Matteo Aldeghi, Alán Aspuru-Guzik
Model-based optimization strategies, such as Bayesian optimization (BO), have been deployed across the natural sciences in design and discovery campaigns due to their sample efficiency and flexibility. The combination of such strategies with automated laboratory equipment and/or high-performance computing in a…