Adaptive drift diffusion process to learn time intervals

(PDF) Adaptive Drift-Diffusion Process to Learn Time Intervals

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The Time-adaptive DDM (TDDM) explains timing as the result of a noisy drift-diffusion process with an adaptive drift rate, which is adjusted based on the time interval observed. ...

(PDF) Adaptive Drift-Diffusion Process to Learn Time Intervals

Adaptive Drift-Diffusion Process to Learn Time Interval

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Adaptive Drift-Diffusion Process to Learn Time Intervals Francois Rivest1 Yoshua Bengio Département d'informatique et de recherche opérationnelle Université de Montréal francois.rivest@mail.mcgill.ca bengioy@iro.umontreal.ca Abstract Animals learn the timing between …

Adaptive Drift-Diffusion Process to Learn Time Interval

Adaptive drift-diffusion process to learn time intervals

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Adaptive Drift-Diffusion Process to Learn Time Intervals Francois Rivest1 Yoshua Bengio Département d'informatique et de recherche opérationnelle Université de Montréal francois.rivest@mail.mcgill.ca bengioy@iro.umontreal.ca Abstract Animals learn the timing between consecutive events very easily.

Adaptive drift-diffusion process to learn time intervals

[1103.2382] Adaptive Drift-Diffusion Process to Learn Time ...

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Current adaptive recurrent neural networks fail at learning to predict the timing of future events (the 'when') in a realistic manner. In this paper, we present a new model of interval timing, based on simple temporal integrators, derived from drift-diffusion models. We develop a simple geometric rule to learn 'when' instead of 'what'.

[1103.2382] Adaptive Drift-Diffusion Process to Learn Time ...

[1103.2382] Adaptive Drift-Diffusion Process to Learn Time ...

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Current adaptive recurrent neural networks fail at learning to predict the timing of future events (the 'when') in a realistic manner. In this paper, we present a new model of interval timing, based on simple temporal integrators, derived from drift-diffusion models. We develop a simple geometric rule to learn 'when' instead of 'what'.

[1103.2382] Adaptive Drift-Diffusion Process to Learn Time ...

An adaptive drift-diffusion model of interval timing dynamics

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These time-adaptive drift-diffusion models (TDDMs) work by accumulating evidence of elapsing time through their drift rate, thereby encoding the to-be-timed interval. One outstanding challenge for these models lies in the dynamics of interval timing—when the to-be-timed intervals are non-stationary.

An adaptive drift-diffusion model of interval timing dynamics

A decision model of timing - ScienceDirect

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A decision model of timing. ... which is equivalent to the adjustment of the clock speed to time different intervals. This puts BeT into the adaptive clock class of timing models. ... F. Rivest, Y. BengioAdaptive drift-diffusion process to learn time intervals. Cornell University Library (2011)

A decision model of timing - ScienceDirect

Learning to Predict Events On-line: A Semi-Markov Model ...

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Section 5 provides a brief conclusions and future work. 2 T h e A lgorithm A fast-learning univariate time-adaptive drift-diffusion model has recently been developed to explain an animal’s rapid adaptation to change in the timing of events [4-6].

Learning to Predict Events On-line: A Semi-Markov Model ...

Interval Timing by Long-Range Temporal Integration

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We have shown Simen et al. that a time-scale-invariant drift–diffusion model of timing arises from counting up the spikes of a Poisson process (rate λ 1), and subtracting off the spikes of an opponent Poisson process with proportionally lower rate γλ 1, λ < 1.

Interval Timing by Long-Range Temporal Integration

Learning to Predict Events On-line: A Semi-Markov Model ...

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These time-adaptive drift-diffusion models (TDDMs) work by accumulating evidence of elapsing time through their drift rate, thereby encoding the to-be-timed interval.

Learning to Predict Events On-line: A Semi-Markov Model ...

Francois Rivest | Royal Military College of Canada ...

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Like Treisman's model, this time-adaptive, opponent Poisson, drift diffusion model (TOPDDM) accounts for timescale invariance without first assuming Weber's law. It also makes new predictions about response times and learning speed and connects interval timing to the popular drift diffusion model (DDM) of perceptual decision making.

Francois Rivest | Royal Military College of Canada ...

Meetup : Houston Meetup - LessWrong 2.0

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10/30/2011 · DISCUSSION ARTICLE FOR THE MEETUP : HOUSTON MEETUP [/MEETUPS/4G] WHEN:30 October 2011 02:00:00PM (-0500) WHERE:2010 Commerce St, Houston, Tx. 77002 After a temporary hiatus, the Houston LW meetup group will reconvene on 10/30 at 2:00 PM. I will be presenting a paper from within my field of research, theoretical neuroscience. The paper, "Adaptive Drift-Diffusion Process to Learn Time Intervals ...

Meetup : Houston Meetup - LessWrong 2.0

Theoretical and Computational Neuroscience Seminar at Univ ...

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Adaptive Drift-Diffusion Process to Learn Time Intervals Francois Rivest Yoshua Bengio (2011) 10/4: Mingbo Cai: A Model of Interval Timing by Neural Integration Patrick Simen, Fuat Balci, Laura deSouza, Jonathan D. Cohen, and Philip Holmes J. Neurosci. (2011) 10/11: Dimitry Yatsenko

Theoretical and Computational Neuroscience Seminar at Univ ...

Elliot Ludvig | University of Warwick - Academia.edu

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These time-adaptive drift-diffusion models (TDDMs) work by accumulating evidence of elapsing time through their drift rate, thereby encoding the to-be-timed interval. One outstanding challenge for these models lies in the dynamics of interval timing-when the to-be-timed intervals are non-stationary.

Elliot Ludvig | University of Warwick - Academia.edu

Francois Rivest - Associate Professor - Royal Military ...

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Drift–diffusion models (DDMs) are a popular framework for explaining response times in decision-making tasks. Recently, the DDM architecture has been used to model interval timing. The Time-adaptive DDM (TDDM) is a physiologically plausible mechanism that adapts in real-time to different time intervals while preserving timescale invariance.

Francois Rivest - Associate Professor - Royal Military ...

Francois Rivest - Associate Professor - Royal Military ...

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View Francois Rivest’s profile on LinkedIn, the world's largest professional community. Francois has 2 jobs listed on their profile. See the complete profile on LinkedIn and discover Francois ...

Francois Rivest - Associate Professor - Royal Military ...

PLOS ONE: Are Accuracy and Reaction Time Affected via ...

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These results are controversial as they undermine the notion that accuracy and reaction time are influenced by the same latent process that underlie the decision process. Typically, accumulation-to-bound models (like the drift diffusion model) can explain variability in both accuracy and reaction time by a change of a single parameter.

PLOS ONE: Are Accuracy and Reaction Time Affected via ...

A Nonparametric Model of Term Structure Dynamics and the ...

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This article presents a technique for nonparametrically estimating continuous‐time diffusion processes that are observed at discrete intervals. We illustrate the methodology by using daily three and six month Treasury Bill data, from January 1965 to July 1995, to estimate the drift and diffusion of the short rate, and the market price of ...

A Nonparametric Model of Term Structure Dynamics and the ...

Elliot Ludvig - Associate Professor - University of ...

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Elliot Ludvig is an associate professor in the psychology department of the University of Warwick,... Elliot Ludvig liked this. As closing part of the neuroeconomics series, I interviewed... Elliot Ludvig is an associate professor in the psychology department of the University of Warwick,...

Elliot Ludvig - Associate Professor - University of ...

Is the Short Rate Drift Actually Nonlinear? - Chapman ...

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Is the Short Rate Drift Actually Nonlinear? David A. Chapman. ... Data driven confidence intervals for diffusion process using double smoothing empirical likelihood, Journal ... ADAPTIVE TESTING IN CONTINUOUS-TIME DIFFUSION MODELS, Econometric Theory, 20, 05, (2004).

Is the Short Rate Drift Actually Nonlinear? - Chapman ...

Francois Rivest - Associate Professor - Royal Military ...

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Découvrez le profil de Francois Rivest sur LinkedIn, la plus grande communauté professionnelle au monde. Francois indique 2 postes sur son profil. Consultez le profil complet sur LinkedIn et découvrez les relations de Francois, ainsi que des emplois dans des entreprises similaires.

Francois Rivest - Associate Professor - Royal Military ...

Elliot Ludvig - Associate Professor - University of ...

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Bekijk het profiel van Elliot Ludvig op LinkedIn, de grootste professionele community ter wereld. Elliot Ludvig heeft 5 functies op zijn of haar profiel. Bekijk het volledige profiel op LinkedIn om de connecties van Elliot Ludvig en vacatures bij vergelijkbare bedrijven te zien.

Elliot Ludvig - Associate Professor - University of ...

Exact Bayesian inference for animal movement in continuous ...

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8/19/2015 · While it is natural to think of the underlying movement process of an animal as taking place in continuous time (Harris & Blackwell 2013; Fleming et al. 2014a), the majority of analysis is based on inherently discrete models, in which the (usually arbitrary) …

Exact Bayesian inference for animal movement in continuous ...

Practitioners’ Corner | Journal of Financial Econometrics ...

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The first method assumes that the drift is linear, as in Aït-Sahalia (1996a) and estimates the diffusion function nonparametrically. The asymptotic properties of this semiparametric estimator do not depend on the discretization parameter of the Euler first-order approximation of the continuous-time process.

Practitioners’ Corner | Journal of Financial Econometrics ...

Invariant feature extraction from event based stimuli

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Generative Adaptive Subspace Self-Organizing Map ... An obvious way to process event based data is to accumulate events over fixed time intervals to recreate frames, and then extract information from the recreated frames using ...

Invariant feature extraction from event based stimuli

Elliot Ludvig - Associate Professor - University of ...

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Elliot Ludvig adlı kişinin profilinde 5 iş ilanı bulunuyor. LinkedIn‘deki tam profili ve Elliot Ludvig adlı kullanıcının bağlantılarını ve benzer şirketlerdeki işleri görün. En büyük profesyonel topluluk olan LinkedIn‘de Elliot Ludvig adlı kullanıcının profilini görüntüleyin.

Elliot Ludvig - Associate Professor - University of ...

Elliot Ludvig – Associate Professor – University of ...

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Sehen Sie sich das Profil von Elliot Ludvig auf LinkedIn an, dem weltweit größten beruflichen Netzwerk. 5 Jobs sind im Profil von Elliot Ludvig aufgelistet. Sehen Sie sich auf LinkedIn das vollständige Profil an. Erfahren Sie mehr über die Kontakte von Elliot Ludvig und über Jobs bei ähnlichen Unternehmen.

Elliot Ludvig – Associate Professor – University of ...

Elliot Ludvig - Associate Professor - University of ...

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Vis Elliot Ludvigs profil på LinkedIn, verdens største faglige nettverk. Elliot har 5 jobber oppført på profilen. Se hele profilen på LinkedIn og finn Elliots forbindelser og jobber i tilsvarende bedrifter.

Elliot Ludvig - Associate Professor - University of ...

Elliot Ludvig – Associate Professor – University of ...

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I build computer models of how humans and other animals learn to make decisions. ...

Elliot Ludvig – Associate Professor – University of ...

Elliot Ludvig - Associate Professor - University of ...

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I build computer models of how humans and other animals learn to make decisions. Experience. University of Warwick ...

Elliot Ludvig - Associate Professor - University of ...
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