Top Tweets for #AlgorithmicDifferentiation
Congrats, Maicon Hieronymus @uni_mainz_eng, Manuel Baumgartner @DWD_presse, Annette Miltenberger and André Brinkmann @uni_mainz_eng for your latest article on #AlgorithmicDifferentiation for Sensitivity Analysis in #CloudMicrophysics”!
https://t.co/zkC2JoUFPR
AAD can provide computational savings whilst delivering stable and accurate first and second order sensitivities.
https://t.co/wrVm7p96qy
#riskmanagement #algorithmicdifferentiation #AAD #Quant #Trading #algorithmictrading #algorithms #electronictrading #finance #Risk
Good morning. We're at @QuantMinds come visit the @NAGTalk virtual booth - #AlgorithmicDifferentiation #machinelearning #quantitativefinance #innovation
#cloud #hpc #NAGLibrary #quant https://t.co/HoIV6MtzCY
And another #paper accepted!
"Towards #compiler-aided correctness checking of #adjoint #MPI applications" was accepted at the #correctness20 workshop.
#hpc #ad #algorithmicdifferentiation
Lots of reading material in today’s NAGNews: Accelerating #Bayesian with #AlgorithmicDifferentiation, ARM Cost of Solution for #HPC, Azure #MachineLearning Tutorial and an #Optimization Collaboration – take a look https://t.co/Z80jzn0gaf and happy reading!
Second @NAGTalk #AlgorithmicDifferentiation Masterclass Series announced – open for delegate registration now – save your seat at the highly successful AD online learning event https://t.co/I7xtT8bqHo
#quants #quantitativefinance #machinelearning #montecarlo
Computing Jacobians and the joys of....... the tangent mode. Check out these two great #AlgorithmicDifferentiation blogs. Great work by Jacques du Toit supporting the AD Masterclass delivery led by Viktor Mosenkis #hpc #quantitativefinance https://t.co/kz8eC94RGj
My boss promised me that I would work on some #AlgorithmicDifferentiation at some point.
I'm currently co-authoring a paper that target's the #AD domain. So, I guess, it eventually happened. :D
Also relevant to #HPC :)
The feedback I received from a colleague who attends the class is very positive! Very good job.
Maybe also interesting for #hpc folks who want to use #AlgorithmicDifferentiation #AutoDiff
Great #AlgorithmicDifferentiation Masterclass feedback - still time to catch-up and attend https://t.co/9vLLaZdigN. A unique (and free) opportunity to learn extensively about AD. Attendee questions covered in these post-class blogs https://t.co/ik7BoollpW #learning #programming
Register for this unique opportunity to receive expert #AlgorithmicDifferentiation instruction - the online AD Masterclass series is free to attend - move beyond examples and PoCs to real-world codes
Learn more https://t.co/9vLLaZdigN starts 30 July!
#programming #quants
CppAD. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. Tape. Retape. I literally have no idea what I'm doing. #algorithmicdifferentiation
See now NAG’s Algorithmic Differentiation tool - dco/c++ - helped Team Sonnenwagen from @RWTH optimize solar racing car aerodynamics in our latest news roundup https://t.co/yd2kftyZVs
#TechNews #AlgorithmicDifferentiation #SolarCar #SolarRacing
NatWest Quant Conference – Viktor of @NAGTalk presents #AlgorithmicDifferentiation and #CVA https://t.co/a4r4Ce4hxZ
NAG AD collaborator, Prof Naumann opens the Computational & Numerical efficiency stream at #QuantMinds with his talk on Global #Adjoints in Vienna this morning - learn more here https://t.co/K1gkddgtQX #AlgorithmicDifferentiation #quant
dco/map is used to create adjoints of performance-critical sections of code, be they C++/OpenMP or CUDA – learn more https://t.co/FtjgkJQg7K
#AlgorithmicDifferentiation #XVA
We are excited to announce a host of improvements to our cross-platform, accelerator ready Adjoint Algorithmic Differentiation (AAD) Tool, dco/map – learn more https://t.co/FtjgkJQg7K
#AlgorithmicDifferentiation #XVA
NAG #Quant Finance News – Winter 2018
- my favourites:
•Adjoint solvers in the NAG Library - #AlgorithmicDifferentiation
• #CVA at Scale
• #NAGLibrary for #Python
•NAG's #HPC Role in EU POP Project continues https://t.co/W2Sndu274Q
.@NAGTalk collaborator Prof. Uwe Naumann writes for @QuantMinds 'Lessons from 10+ years of Algorithmic Differentiation in computational finance' #AlgorithmicDifferentiation
"Due to the necessary reversal of the data flow AAD is known to suffer from potentially prohibitive memory requirement when applied naively to nontrivial numerical simulations" #AlgoTrading #eTrading https://t.co/vHv4P2ZqSD
Latest tech posters from NAG being shown here in Nice for WBS 14th Quant Finance conference. https://t.co/kz9FgDmQHz
#AlgorithmicDifferentiation #Quants #CVA #XVA #FRTB #NAGLibrary (inc. Mathematical Optimization, PDEs, Nearest Correlation Matrix), and…https://t.co/y0E6LfYntQ
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