Meeting Notes 23.03.2022

Meeting Details

Date : 23 March 2021

Time : 10:00 – 11:00

Location : Chair of CPS, Montanuniverität Leoben

Participants: Univ.-Prof. Dr. Elmar Rueckert, Fotios Lygerakis


  1. Discuss idea for adding contrastive loss to a(n) (variational)autoencoder
  2. Getting started with real robots

Topic 1: Discuss idea for adding contrastive loss to a(n) (variational) autoencoder

  • Test different architectures
    • Compare the proposed architecture(contrastive AE) with normal contrastive or (V)AEs
    • (future) integrateprior knowledge
  • Explore different ways to update the weights (gradient flow)
    • contrastive loss flows or not through the decoder
  • check the learning stability
    • we need stable update rules
  • Derive the equations from Information Theoretic Principles
    • e.g. ELBO

Topic 2: Getting started with real robots

  • Talk with Vedant and join his project
  • Do the FE tutorials on Gazebo

Next Steps

  • Derive the Information Theoretic equations
  • Start building AEs and Contrastive loss networks
  • Do the FE Panda tutorials


[1] Srinivas, Aravind, Michael Laskin, and Pieter Abbeel. “Curl: Contrastive
unsupervised representations for reinforcement learning.” arXiv preprint arXiv:2004.04136 (2020).

[2] https://www.deeplearningbook.org/contents/autoencoders.html

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