Multi-Object Representation Learning with Iterative Variational Inference. - Klaus Greff; Raphaël Lopez Kaufman; Rishabh Kabra; Nick Watters; Chris Burgess 001; Daniel Zoran; Loic Matthey; Matthew M. Botvinick; Alexander Lerchner (ICML, 2019)

An Investigation of Model-Free Planning. - Arthur Guez; Mehdi Mirza; Karol Gregor; Rishabh Kabra; Sébastien Racanière; Theophane Weber; David Raposo; Adam Santoro; Laurent Orseau; Tom Eccles; Greg Wayne; David Silver; et al. (ICML, 2019)

MONet: Unsupervised Scene Decomposition and Representation. - Christopher P. Burgess; Loïc Matthey; Nicholas Watters; Rishabh Kabra; Irina Higgins; Matthew M. Botvinick; Alexander Lerchner (CoRR, 2019)

AlignNet: Unsupervised Entity Alignment. - Antonia Creswell; Kyriacos Nikiforou; Oriol Vinyals; Andre Saraiva 001; Rishabh Kabra; Loic Matthey; Chris Burgess 001; Malcolm Reynolds; Richard Tanburn; Marta Garnelo; Murray Shanahan (CoRR, 2020)

PARTS: Unsupervised segmentation with slots, attention and independence maximization. - Daniel Zoran; Rishabh Kabra; Alexander Lerchner; Danilo J. Rezende (ICCV, 2021)

Unsupervised Object-Based Transition Models For 3D Partially Observable Environments. - Antonia Creswell; Rishabh Kabra; Christopher P. Burgess; Murray Shanahan (NeurIPS, 2021)

SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition. - Rishabh Kabra; Daniel Zoran; Goker Erdogan; Loic Matthey; Antonia Creswell; Matt M. Botvinick; Alexander Lerchner; Christopher P. Burgess (NeurIPS, 2021)

Constellation: Learning relational abstractions over objects for compositional imagination. - James C. R. Whittington; Rishabh Kabra; Loic Matthey; Christopher P. Burgess; Alexander Lerchner (CoRR, 2021)

Evaluating VLMs for Score-Based, Multi-Probe Annotation of 3D Objects. - Rishabh Kabra; Loic Matthey; Alexander Lerchner; Niloy J. Mitra (CoRR, 2023)

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

Moving Off-the-Grid: Scene-Grounded Video Representations. - Sjoerd van Steenkiste; Daniel Zoran; Yi Yang 007; Yulia Rubanova; Rishabh Kabra; Carl Doersch; Dilara Gokay; Joseph Heyward; Etienne Pot; Klaus Greff; Drew A. Hudson; Thomas Keck; et al. (NeurIPS, 2024)

Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models. - Ziyi Wu; Yulia Rubanova; Rishabh Kabra; Drew A. Hudson; Igor Gilitschenski; Yusuf Aytar; Sjoerd van Steenkiste; Kelsey R. Allen; Thomas Kipf (NeurIPS, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)

Probabilistic Inverse Cameras: Image to 3D via Multiview Geometry. - Rishabh Kabra; Drew A. Hudson; Sjoerd van Steenkiste; João Carreira 001; Niloy J. Mitra (CoRR, 2024)

Scaling 4D Representations. - João Carreira 001; Dilara Gokay; Michael King; Chuhan Zhang; Ignacio Rocco; Aravindh Mahendran; Thomas Keck; Joseph Heyward; Skanda Koppula; Etienne Pot; Goker Erdogan; Yana Hasson; et al. (CoRR, 2024)

From Image to Video: An Empirical Study of Diffusion Representations. - Pedro Vélez; Luisa F. Polanía; Yi Yang 007; Chuhan Zhang; Rishabh Kabra; Anurag Arnab; Mehdi S. M. Sajjadi (CoRR, 2025)

OpenWorldSAM: Extending SAM2 for Universal Image Segmentation with Language Prompts. - Shiting Xiao; Rishabh Kabra; Yuhang Li 001; Donghyun Lee 002; João Carreira 001; Priyadarshini Panda (CoRR, 2025)

Generalist Forecasting with Frozen Video Models via Latent Diffusion. - Jacob C. Walker; Pedro Vélez; Luisa Polania Cabrera; Guangyao Zhou; Rishabh Kabra; Carl Doersch; Maks Ovsjanikov; João Carreira 001; Shiry Ginosar (CoRR, 2025)