Budapest University of Technology and Economics
Modelling of stochastic effects in engineering is limited not only by the few existing mathematical methods but also by their low effectivity and high complexity. An easy-to-use Julia package is presented to investigate stochastic linear delayed systems including control and machine-tool vibrations.
GERAD, Montréal & INRIA Lille
Increasing the proportion of renewable energy has become a priority for power grids, but their integration requires higher flexibility of consumption times. Using game theory and optimization, we design a framework allowing flexibility and privacy, while reducing costs for both consumer and supplier
ETH Zurich, Switzerland
Glaciers and ice caps are projected to dominate global sea level rise up to 2100. To estimate ice thickness maps of such glaciers using mostly surface data, we use a semi-physical forward model combined with a Bayesian inversion scheme. We leverage Julia to allow compute intense MCMC simulations.
Dravyaniti Consulting LLP
Life of a Trading strategy is unknown. 'Till how long will this work?'. As markets get more mature, with advent of ML and AI, the designer's job is getting tougher. Using rules to analyse big data by splitting it across Time-Frames, traders can gain significant edges, for all types of traders.
University of Luxembourg
Julia accelerates analyses of huge-scale biochemical networks with now more than a million biochemical reactions. Through the open-source high-performance COBRA.jl package, the analysis capabilities of the COnstraint-Based Reconstruction and Analysis community are lifted to another level.
British Antarctic Survey
EchoJulia is a software library that is enabling new kinds of fisheries acoustic applications. From big data analysis of ship-based surveys to data collection from ocean gliders, we show how Julia is set to improve ecosystem estimates of Southern Ocean Antarctic Krill.
University College London
Handling uncertainty in process design and optimisation is a crucial challenge in current research and in the industry. We believe that Julia has the potential to be used as a comprehensive modelling language to enable designers to develop new systems with greater confidence.
Australian Institute for Machine Learning
I will present an approximate maximum likelihood method that encapsulates a gamut of heteroscedastic errors-in-variables regression problems that often arise in computer vision applications. Julia's multiple dispatch and Unicode support facilitates a unique, concise and readable implementation.
University of Warwick
Most of the time, neurons in the cortex fire due to randomly arriving inputs. The irregular firing that results is not merely noise, but is thought to play an important role in cortical computation. I show how I have implemented stochastic simulations of this irregular firing in my research.
Exegetic Analytics
Bayesian techniques can seem challenging and esoteric. However, they promise a powerful alternative to frequentist statistics, with the possibility of extracting even more useful information from your data. This talk will help you get started with Bayesian analyses.
Institute for Economic Forecasting, Romanian Academy
The title of the presentation comes from the my forthcoming book at one of the leading publishers, Academic Press, an imprint of Elsevier. The poster (based on the book) will introduce the audience to state-of-art computational techniques used in economics through examples and applications in Julia.
City of London School
The talk is about remote control robots controlled by Julia on a Raspberry Pi. I will show how to do physical computing with Julia using the GPIO pins of the Pi.
UNAM
Julia's capabilities are amazing for scientific computing - but how to begin designing your own libraries and packages? With OrthogonalPolynomials.jl, we will showcase the development of a production ready library in 100 lines of code - with a series of video walkthroughs on step by step design.
UFPR - Federal University of Paraná
We study the Simplex method, a linear optimization search method. The revised Simplex method was studied and implemented along with the LU update, aiming for the solution of large scale sparse problems. The method was implemented in the Julia Language and tested against available solvers.
Karlsruhe Institute of Technology
This poster announces PCE.jl, which is a Julia Package for uncertainty quantification (UQ) using a method called 'polynomial chaos expansion' (PCE). It offers an alternative approach to Monte-Carlo-based UQ, and is also more efficient for certain problem instances.
University of Cambridge
Deep Learning's popularity is partly derived from its composability. General probabilistic machine learning is, in fact, just as composable, but technically much more challenging. I present an interesting edge case where life is easy, and discuss how Julia is uniquely positioned to exploit this.
University of California, Irvine
Stochasticity (randomness) in biochemical reactions exists. Things diffuse and randomly bump together to bind/unbind. Yet these chemicals form the basis of life. But biological organisms evolve to their surroundings. Have they evolved to use biochemical randomness? I will demonstrate how they do it.
