Lerchner, Alexander

15 publications

TMLR 2025 Exploring Exploration with Foundation Agents in Interactive Environments Daniel P. Sawyer, Nan Rosemary Ke, Hubert Soyer, Martin Engelcke, John Reid, David P Reichert, Drew A. Hudson, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P Lillicrap, Michael Curtis Mozer, Jane X Wang

ICCV 2025 LayerLock: Non-Collapsing Representation Learning with Progressive Freezing Goker Erdogan, Nikhil Parthasarathy, Catalin Ionescu, Drew A. Hudson, Alexander Lerchner, Andrew Zisserman, Mehdi S. M. Sajjadi, Joao Carreira

ICML 2024 Leveraging VLM-Based Pipelines to Annotate 3D Objects Rishabh Kabra, Loic Matthey, Alexander Lerchner, Niloy Mitra

CVPR 2024 SODA: Bottleneck Diffusion Models for Representation Learning Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner

NeurIPSW 2023 Evaluating VLMs for Score-Based, Multi-Probe Annotation of 3D Objects Rishabh Kabra, Loic Matthey, Alexander Lerchner, Niloy Mitra

LoG 2022 Reasoning-Modulated Representations Petar Veličković, Matko Bošnjak, Thomas Kipf, Alexander Lerchner, Raia Hadsell, Razvan Pascanu, Charles Blundell

ICCV 2021 PARTS: Unsupervised Segmentation with Slots, Attention and Independence Maximization Daniel Zoran, Rishabh Kabra, Alexander Lerchner, Danilo J. Rezende

NeurIPS 2021 SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition Rishabh Kabra, Daniel Zoran, Goker Erdogan, Loic Matthey, Antonia Creswell, Matt Botvinick, Alexander Lerchner, Chris Burgess

ICLR 2020 Unsupervised Model Selection for Variational Disentangled Representation Learning Sunny Duan, Loic Matthey, Andre Saraiva, Nicholas Watters, Christopher P. Burgess, Alexander Lerchner, Irina Higgins

ICML 2019 Multi-Object Representation Learning with Iterative Variational Inference Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Christopher Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, Alexander Lerchner

ICLRW 2019 Spatial Broadcast Decoder: A Simple Architecture for Disentangled Representations in VAEs Nick Watters, Loic Matthey, Chris P. Burgess, Alexander Lerchner

NeurIPS 2018 Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies Alessandro Achille, Tom Eccles, Loic Matthey, Chris Burgess, Nicholas Watters, Alexander Lerchner, Irina Higgins

ICLR 2018 SCAN: Learning Hierarchical Compositional Visual Concepts Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P Burgess, Matko Bošnjak, Murray Shanahan, Matthew Botvinick, Demis Hassabis, Alexander Lerchner

ICLR 2017 Beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework Irina Higgins, Loïc Matthey, Arka Pal, Christopher P. Burgess, Xavier Glorot, Matthew M. Botvinick, Shakir Mohamed, Alexander Lerchner

ICML 2017 DARLA: Improving Zero-Shot Transfer in Reinforcement Learning Irina Higgins, Arka Pal, Andrei Rusu, Loic Matthey, Christopher Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, Alexander Lerchner