Marco Fraccaro

Machine learning researcher

[Marco Fraccaro @fraccarom]

My PhD thesis on "Deep Latent Variable Models for Sequential Data" is finally online! If you want to learn how VAEs can be extended to the sequential setting you should check it out: https://t.co/uL1JoeUcWI
Special thanks to my amazing supervisors @OleWinther1 @ulrichpaquet

[Marco Fraccaro @fraccarom]

Really cool to see deep sequential latent variable models used to learn to fly real drones - not in a simulated environment!!

[Justin Bayer @usuallyuseless]

Variational state-space models can be used to perform optimal control of drones only equipped with LiDARs. So show my dear colleagues Philip Becker-Ehmck and Max Karl in their latest work "Learning to fly". https://t.co/z4SArO8X2M. Thread.

[Marco Fraccaro @fraccarom]

You can also try BIVA yourself, with our Tensorflow AND PyTorch implementations!
Tensorflow code: https://t.co/QM48zughcn
PyTorch code: https://t.co/y3l8JTGuFR

[Marco Fraccaro @fraccarom]

VAEs enthusiasts, if you are at #NeurIPS2019 you should come to poster 110 today at 10.45. We'll be presenting BIVA, and show you how to build powerful deep hierarchical VAEs. 
Paper: https://t.co/00oS0SwFji

@larsmaaloe @valentinlievin @OleWinther1

[Marco Fraccaro @fraccarom]

It was a pleasure to talk about deep latent variable models at the summer school on generative models by @DTU_Compute and @uni_copenhagen! If none among the 1000s of VAE tutorials out there is good enough for you, try my slides https://t.co/RB5yYeTmmP

[Lars Kai Hansen @Tweetteresearch]

Be part of the expanding AI hub in Copenhagen - 12 Postdoc positions as part of multidisciplinary university collaboration. DM if you are interested https://t.co/W7Quaxz5zY @DTUtweet @DTU_Compute @jan_madsen

[Marco Fraccaro @fraccarom]

Great to see this working with multiple objects!

[Silvia Chiappa @csilviavr]

New paper with @ulrichpaquet using exact temporal inference for learning the dynamics of moving objects from pixels.

[Yarin @yaringal]

Really excited to release Bayesian Deep Learning Benchmarks - please share with others who you think might like this, and have a look at the blog/repo/colab:
https://t.co/ZKqN40da1S
This work was done over a period of a year and a half by many collaborators @OATML_Oxford

[Martina Fischetti @MartiFischetti]

My PhD in a minute 😊 Thanks @Vattenfall_DK #phd1minute #orms #appliedOR #operationsresearch #GreenEnergy

[Jakub Tomczak @jmtomczak]

This paper: https://t.co/U9BVT5Bwk7 (by @larsmaaloe @fraccarom @LieValentin & @OleWinther1) was put on arXiv two days ago and it was already discussed at @UvA_Amsterdam. It is wonderful and extremely well-written, all experiments are carefully carried out. Highly recommended!

[Marco Fraccaro @fraccarom]

@jmtomczak @larsmaaloe @LieValentin @OleWinther1 @UvA_Amsterdam Thanks! Glad you liked it

[Marco Fraccaro @fraccarom]

"BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling". A skip-connected generative model and a bidirectional inference network are all you need! Work with @larsmaaloe @LieValentin @OleWinther1
https://t.co/Q7bM7OQbcr

[Papers with Code @paperswithcode]

We’ve just released the new Papers With Code! Site now has over 950+ ML tasks, 500+ evaluation tables (including state of the art results) and 8500+ papers with code. Explore the resource here: https://t.co/stfzzn0IfM. Have fun!

[Martina Fischetti @MartiFischetti]

Excited to announce that the project I am leading in #Vattenfall is among the 2019 @INFORMS Franz Edelman Award finalists!Thanks to #orms, @VattenfallBXL saved $170 million in offshore wind, thus contributing to a fossil free future.With Kristoffersen,Hjort,Pisinger,@mmonaci74

[Ulrich Paquet @ulrichpaquet]

Making probabilistic deep generative models... compositional!
With Sumedh K. Ghaisas and Olivier Tieleman @DeepMindAI. Finally out on arXiv today 😀.
https://t.co/E3TCZOjJEe

[Ulrich Paquet @ulrichpaquet]

For the technically-minded: Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models https://t.co/fOBEM8dLBo An (old) tech report with my good friend @fraccarom, finally seeing the arXiv light of day!! 😀

[Matteo Fischetti @MFischetti]

.@MartiFischetti @fraccarom @mmonaci74 and David Pisinger won the 2018 AIRO Best Application-Oriented Paper award for their work on wind-farm optimization #ods2018 #orms

[Ali Eslami @arkitus]

Come see our poster on Generative Temporal Models at @icmlconf: Hall B poster 101. @fraccarom woop woop!

[Marco Fraccaro @fraccarom]

Great work by @arkitus @DeepSpiker @fabiointheuk! GQNs are also an important component of our latest ICML paper on generative temporal models with spatial memory! https://t.co/pZwppBcxQE

[Ali Eslami @arkitus]

"Neural scene representation and rendering" now in @sciencemagazine. By training deep networks to predict what scenes look like from new viewpoints, we get them to understand images: https://t.co/BwIORXQIGe @DeepSpiker @OriolVinyalsML @theophaneweber @demishassabis

[Danilo J. Rezende @DaniloJRezende]

The paper Generative Temporal Models with Spatial Memory for Partially Observed Environments https://t.co/japUAWhYzu was accepted as a long talk at @icmlconf Congrats again @fraccarom ! https://t.co/csl4sEzNNx