Université de Montréal

About: Université de Montréal is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 45641 authors who have published 100476 publications receiving 4004007 citations. The organization is also known as: University of Montreal & UdeM.

Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription

Abstract: We investigate the problem of modeling symbolic sequences of polyphonic music in a completely general piano-roll representation. We introduce a probabilistic model based on distribution estimators conditioned on a recurrent neural network that is able to discover temporal dependencies in high-dimensional sequences. Our approach outperforms many traditional models of polyphonic music on a variety of realistic datasets. We show how our musical language model can serve as a symbolic prior to improve the accuracy of polyphonic transcription.

Tight bounds on quantum searching

Abstract: We provide a tight analysis of Grover's recent algorithm for quantum database searching. We give a simple closed-form formula for the probability of success after any given number of iterations of the algorithm. This allows us to determine the number of iterations necessary to achieve almost certainty of finding the answer. Furthermore, we analyse the behaviour of the algorithm when the element to be found appears more than once in the table and we provide a new algorithm to find such an element even when the number of solutions is not known ahead of time. Using techniques from Shor's quantum factoring algorithm in addition to Grover's approach, we introduce a new technique for approximate quantum counting, which allows to estimate the number of solutions. Finally we provide a lower bound on the efficiency of any possible quantum database searching algorithm and we show that Grover's algorithm nearly comes within a factor 2 of being optimal in terms of the number of probes required in the table.

Inactivation of Rho Signaling Pathway Promotes CNS Axon Regeneration

Abstract: Regeneration in the CNS is blocked by many different growth inhibitory proteins. To foster regeneration, we have investigated a strategy to block the neuronal response to growth inhibitory signals. Here, we report that injured axons regrow directly on complex inhibitory substrates when Rho GTPase is inactivated. Treatment of PC12 cells with C3 enzyme to inactivate Rho and transfection with dominant negative Rho allowed neurite growth on inhibitory substrates. Primary retinal neurons treated with C3 extended neurites on myelin-associated glycoprotein and myelin substrates. To explore regeneration in vivo, we crushed optic nerves of adult rat. After C3 treatment, numerous cut axons traversed the lesion to regrow in the distal white matter of the optic nerve. These results indicate that targeting signaling mechanisms converging to Rho stimulates axon regeneration on inhibitory CNS substrates.