Posts by Collection


I got accepted into the SCIoI Excellence Cluster!


I got accepted into the Science of Intelligence Excellence Cluster! Starting in October 2019 I will be working on the project “Learning of Intelligent Swarm Behavior” under the supervision of Henning Sprekeler and Pawel Romanczuk. I am very happy to receive such generous funding and support from the excellence cluster.

I will stay affiliated with the Einstein Center for Neurosciences. Furthermore, my work will combine strong evidence from cognitive neuroscience and animal psychology in order to study the computational basis of coordination and adaptation in large collectives.

I will be giving a Talk @ENCODS FENS PhD Symposium!


I am happy to announce that I will be giving a short talk at the ENCODS FENS PhD Symposium about the “Neural Suprise in Human Somatosensation” project I have been working on during my first ECN lab rotation together with Sam Gijsen, Miro Grundei, Dirk Ostwald and Felix Blankenburg. If you are interested in more details and the general paradigm, check out our GitRepo.

RAAI Conference & EEML - I am coming!


Bucharest - I am coming! Very happy to attend the Recent Advances in Artificial Intelligence conference from 28th to 30th of June. I will present my work on Deep Multi-Agent RL for swarm dynamics in a poster session. Furthermore, my work has also been selected to be presented at the super-duper awesome EEML summer school. Can’t wait to meet the hero of temporal abstractions Doina Precup and Mr “Policy Distillation” Andrei Rusu.

Kick-Off ‘Flexible Learning’ Reading Group @TUBerlin


Last week we got to kick-off our new “Flexible Learning” reading group at the Technical University Berlin where we cover recent papers in Meta-/Transfer-/Continual & Self-supervised Learning! We started by reading the latest first-author paper by Yoshua Bengio connecting Meta-Learning with causal inference.

You can join our mailing list for more infos: click here.

Here are all the relevant infos for the next meeting:

Massive thanks goes out to the co-organizing help of Thomas Goerttler, Joram Keijser & Nico Roth! Hit me up if you are interested in joining!

Action Grammars are going to CCN!


Super exciting news! Parts of my masters’s thesis project (supervised by Professor Aldo Faisal) got accepted at the Cognitive Computational Neuroscience conference 2019. We combine Hierarchical Reinforcement Learning & Grammar Induction to define a set of temporally-extended actions… aka an Action Grammar! The resulting temporal abstractions can be used to efficiently tackle imitation, transfer and online learning.

Check out the preprint here! I am still in the process of extending the experiments and already looking forward to the poster presentations in Berlin (13th to 16th of September). The code will be open sourced as well. Hit me up if you are interested in the full story!

OIS Award Final Pitch Selection!


I am really excited to share that my project proposal on “Deep Swarm Shepherding - Benevolent Adaptation of Collective Behavior” has been selected for the final round of the Open Innovation in Science Award of the Einstein Center for Neurosciences Berlin. The goal of the award is to facilitate projects which fuse Open Innovation and Open Science in the context of neuroscience. It is jointly co-organized by the Ludwig Boltzmann Gesellschaft’s Open Innovation in Science Center (LBG OIS Center), QUEST and SPARK-Berlin.

I am very honored and am looking forward to all the 3 minute pitches! If you are interested in learning more about how I intend to make the world a better place by combining Behavioral Tracking, Inverse Reinforcement Learning and Machine Theory of Mind come by. The final round of the selection process will be publicly carried out - here are all the key information:

  • Location: Charité Campus Mitte, Charité CrossOver (CCO), Charitéplatz 1, 10117 Berlin.
  • Date and Time: Thursday, October 10, 2019, 16:00-18:15 (official part), doors open at 15:45.

Action Grammars @NeurIPS Workshops!


Super excited to share that my Master’s thesis project with Aldo Faisal got accepted to both the ‘Deep Reinforcement Learning’ & the ‘Learning Transferable Skills’ Workshop at NeurIPS 2019. I will be presenting the work within the DRL workshop in Vancouver and December!

Check out the updated preprint here & let me know if you have any ideas/questions. Furthermore, code to replicate the results may be found here.

Love, Rob

P.S.: Here is my previous poster from CCN:

Rob joins for.AI :heart:


I am really excited to announce that I have joined for.AI as an independent researcher. for.AI is a mainly-remote coordinated international group of ML researchers. One aim - the production of useful & effective ML research.

I am very much looking forward to new ideas, enthusiastic discussions and fruitful collaborations :hugs:! Such a great idea for the 21st century!

Love, Rob

P.S.: You can check out my solution to the coding challenge (comparing different pruning techniques) here!

Visual-ML-Notes Launch :pencil2:


Really happy to share Visual-ML-Notes ✍️ a virtual gallery of sketchnotes taken at Machine Learning talks 🧠🤓🤖 which includes last weeks #ICLR2020.

Explore, exploit & feel free to share: :point_right: website 💻 & the repository 📝



P.S.: There will be an entire blogpost dedicated to how I go about sketching, the workflow and the post-processing. Stay tuned :heart:

Rob @Virtual MLSS :school:


I am really happy to be attending the virtual edition of the MLSS Tübingen summer school where I will be presenting my most recent work on ‘Time Limits in Meta-Reinforcement Learning’. Get in touch if you want to chat about science, arts and ethology! Also I am looking forward to adding a new album to #visual-ml-notes 📝



Rob’s 1st Podcast - ML Street Talk :microphone:


Dear virtual world,

Last week I got to do my very first podcast. Exciting, right? I had a great time discussing my journey from Econ to ML & Collective Behaviour, social notions of intelligence & the Lottery Ticket Hypothesis! Thanks for having a podcast newbie! Checkout the full podcast by Tim Scarfe, Connor Shorten and Yannic Kilcher here:



Learning not to Learn @MetaLearning NeurIPS Workshop


I very happy to be presenting my recent work on “Learning not to learn: Nature versus nurture in silico” at the NeurIPS Meta Learning workshop. We investigate the interplay of ecological uncertainty, task complexity and expected lifetime on the amortized Bayesian inference performed by memory-based meta learners. Checkout the preprint and feel free to drop me a note or hangout at the poster sessions on December, 11th.

Rob @Virtual M2L :school:


Happy new year! I am really happy to be attending the virtual (and first) edition of the Mediterranean Machine Learning (M2L) summer school. Get in touch if you want to chat about JAX, evolutionary algorithms or meta-learning! And stay tuned for some new #visual-ml-notes 📝 Big thank you to the organizers!





RandNLA for Generalized Linear Models with Big Datasets

Published in UPF/UAB Public Online Repository, 2017

Barcelona GSE Masters Thesis which generalizes RandNLA to GLMs.

Recommended citation: Lange, Robert Tjarko. (2017). "Randomized Numerical Linear Algebra for Generalized Linear Models with Big Datasets." UPF/UAB Public Online Repository.

Action Grammars: A Grammar Induction-Based Method for Learning Temporally-Extended Actions

Published in Best (Applied) MAC/MRes/Specialism Project, Sponsored by Winton Capital at Imperial College London, 2018

Imperial College London Masters Thesis which provides a Context-Free Grammar based framework for learning temporal abstractions in Hierarchical Reinforcement Learning.

Recommended citation: Lange, Robert Tjarko. (2018). "Action Grammars: A Grammar Induction-Based Method for Learning Temporally-Extended Actions." Imperial College London - DoC - Best (Applied) MAC/MRes/Specialism Project 2018.

Learning not to learn: Nature versus nurture in silico

Published in -, 2020

We investigate the role of ecological uncertainty, task complexity and lifetime on the qualitative differences between meta-learning adaptation strategies.

Recommended citation: Lange, Robert Tjarko and Sprekeler, Henning. (2020). "Learning not to learn: Nature versus Nurture in Silico." arXiv. Under review..