Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Alexander Lerchner

Alchemy: A structured task distribution for meta-reinforcement learning


Feb 04, 2021
Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, Francis Song, Gavin Buttimore, David P. Reichert, Neil Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matthew Botvinick

* 16 pages, 9 figures 

  Access Paper or Ask Questions

Formalising Concepts as Grounded Abstractions


Jan 13, 2021
Stephen Clark, Alexander Lerchner, Tamara von Glehn, Olivier Tieleman, Richard Tanburn, Misha Dashevskiy, Matko Bosnjak


  Access Paper or Ask Questions

A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning


May 29, 2019
Sunny Duan, Nicholas Watters, Loic Matthey, Christopher P. Burgess, Alexander Lerchner, Irina Higgins


  Access Paper or Ask Questions

COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration


May 22, 2019
Nicholas Watters, Loic Matthey, Matko Bosnjak, Christopher P. Burgess, Alexander Lerchner


  Access Paper or Ask Questions

Multi-Object Representation Learning with Iterative Variational Inference


Mar 01, 2019
Klaus Greff, Raphaël Lopez Kaufmann, Rishab Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, Alexander Lerchner


  Access Paper or Ask Questions

MONet: Unsupervised Scene Decomposition and Representation


Jan 22, 2019
Christopher P. Burgess, Loic Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matt Botvinick, Alexander Lerchner


  Access Paper or Ask Questions

Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs


Jan 21, 2019
Nicholas Watters, Loic Matthey, Christopher P. Burgess, Alexander Lerchner


  Access Paper or Ask Questions

Towards a Definition of Disentangled Representations


Dec 05, 2018
Irina Higgins, David Amos, David Pfau, Sebastien Racaniere, Loic Matthey, Danilo Rezende, Alexander Lerchner


  Access Paper or Ask Questions

Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies


Aug 20, 2018
Alessandro Achille, Tom Eccles, Loic Matthey, Christopher P. Burgess, Nick Watters, Alexander Lerchner, Irina Higgins


  Access Paper or Ask Questions

SCAN: Learning Hierarchical Compositional Visual Concepts


Jun 06, 2018
Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P Burgess, Matko Bosnjak, Murray Shanahan, Matthew Botvinick, Demis Hassabis, Alexander Lerchner


  Access Paper or Ask Questions

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning


Jun 06, 2018
Irina Higgins, Arka Pal, Andrei A. Rusu, Loic Matthey, Christopher P Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, Alexander Lerchner

* ICML 2017 

  Access Paper or Ask Questions

Understanding disentangling in $β$-VAE


Apr 10, 2018
Christopher P. Burgess, Irina Higgins, Arka Pal, Loic Matthey, Nick Watters, Guillaume Desjardins, Alexander Lerchner

* Presented at the 2017 NIPS Workshop on Learning Disentangled Representations 

  Access Paper or Ask Questions

Early Visual Concept Learning with Unsupervised Deep Learning


Sep 20, 2016
Irina Higgins, Loic Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner


  Access Paper or Ask Questions