20 papers · ranked by Valyu relevance
Bo Marr, Jennifer Hasler
A field programmable analog array (FPAA) is presented as an energy and computational efficiency engine: a mixed mode processor for which functions can be compiled at significantly less energy costs using probabilistic computing circuits. More specifically, it will be shown that the core computation of any dynamical…
Christian L. Vestergaard, Mathieu Génois, Marcel Salathé
Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of…
Krishna Rijal, Pankaj Mehta, Anne-Florence Bitbol, Aleksandra M Walczak
'Aleksandra M Walczak'] The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates…
Krishna Rijal, Pankaj Mehta
The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the…
Krishna Rijal, Pankaj Mehta
The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the…
Krishna Rijal, Pankaj Mehta
The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the…
Jaroslav Albert, Ramon Grima
Modeling stochastic behavior of chemical reaction networks is an important endeavor in many aspects of chemistry and systems biology. The chemical master equation (CME) and the Gillespie algorithm (GA) are the two most fundamental approaches to such modeling; however, each of them has its own limitations: the GA may…
David Lacoste, Michele Castellana
We present an improvement of the Gillespie Exact Stochastic Simulation Algorithm, which leverages a bitwise representation of variables to perform independent simulations in parallel. We show that the subsequent gain in computational yield is significant, and it may allow to perform simulations of non-well mixed…
Dipanjana Dalui, John P DeLong
Eco-evolutionary processes drive patterns in species’ abundances and traits. However, modeling complex ecological systems is challenging because of the many species and traits involved and because processes unfold in stochastic and non-equilibrium conditions. Gillespie Eco-evolutionary Models (GEMs) were created to…
Naoki Masuda, Luis E. C. Rocha
The Gillespie algorithm provides statistically exact methods for simulating stochastic dynamics modelled as interacting sequences of discrete events including systems of biochemical reactions or earthquake occurrences, networks of queuing processes or spiking neurons, and epidemic and opinion formation processes on…
Jaroslav Albert
We present a highly efficient and accurate hybrid stochastic simulation algorithm (HSSA) for the purpose of simulating a subset of biochemical reactions of large gene regulatory networks (GRN). The algorithm relies on the separability of a GRN into two groups of reactions, A and B, such that the reactions in A can be…
Naoki Masuda, Christian L. Vestergaard
Many multiagent dynamics, including various collective dynamics occurring on networks, can be modeled as a stochastic process in which the agents in the system change their state over time in interaction with each other. The Gillespie algorithms are popular algorithms that exactly simulate such stochastic multiagent…
Davoud Mirzaei
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Herbert M Sauro
A common approach to simulating chemical reaction systems is to formulate the problem as a set of ordinary differential equation and solve them using standard numerical procedures. Such a formulation works well when the number of molecules involved in the simulation is large and assumes a deterministic formulation for…
Andrew J. Loza, Marc S. Sherman
Biological systems frequently contain biochemical species present as small numbers of slowly diffusing molecules, leading to fluctuations that invalidate deterministic analyses of system dynamics. The development of mathematical tools that account for the spatial distribution and discrete number of reacting molecules…
Chia Ying Lee
In an experimental study of single enzyme reactions, it has been proposed that the rate constants of the enzymatic reactions fluctuate randomly, according to a given distribution. To quantify the uncertainty arising from random rate constants, it is necessary to investigate how one can simulate such a biochemical…
David Alonso, Steffen Bauer, Markus Kirkilionis, Lisa Maria Kreuser + 1 more
'Luca Sbano'] 1Theoretical and Computational Ecology, Center for Advanced Studies of Blanes (CEAB-CSIC), Spanish Council for Scientific Research, Acces Cala St. Francesc 14, Blanes, E-17300, Spain. 2Mathematisches Institut, Mathematikon, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 205, 69120 Heidelberg…
Dileep Kishore, Srikiran Chandrasekaran
Biological systems are intrinsically noisy and this noise may determine the qualitative outcome of the system. In the absence of analytical solutions to mathematical models incorporating noise, stochastic simulation algorithms are useful to explore the possible trajectories of these systems. Algorithms used for such…
Authors not listed
Stochastic Simulation Algorithms (SSA) are a cornerstone in simulating Free Radical Polymerization (FRP) due to their accuracy and reliability. However, computational inefficiency remains a challenge for large-scale and complex polymerization systems. This work introduces a novel stochastic simulation algorithm…
Authors not listed
Identifying synthesis routes from knowledge graphs poses challenges beyond retrosynthesis, including path–finding artifacts and data issues. We introduce “SynGPS”, a novel algorithm that overcomes these limitations by identifying viable routes even with common artifacts. SynGPS can resolve nonsensical cycles…