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Publications

Relational reasoning

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Dual Algorithmic Reasoning
Danilo Numeroso *, Davide Bacciu *, Petar Veličković
ICLR
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Continuous Neural Algorithmic Planners
Yu He *, Petar Veličković, Pietro Liò *, Andreea-Ioana Deac
LoG
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Reasoning-Modulated Representations
Petar Veličković, Matko Bošnjak, Thomas Kipf *, Alexander Lerchner, Raia Hadsell, Razvan Pascanu, Charles Blundell
LoG
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Learning Graph Search Heuristics
Michal Pándy *, Weikang Qiu *, Gabriele Corso *, Petar Veličković, Rex Ying *, Jure Leskovec *, Pietro Liò *
LoG
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Publication
Learnable Commutative Monoids for Graph Neural Networks
Euan Ong *, Petar Veličković
LoG
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A Generalist Neural Algorithmic Learner
Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Dudzik, Matko Bošnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea-Ioana Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Veličković
LoG
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Expander Graph Propagation
Andreea-Ioana Deac, Marc Lackenby *, Petar Veličković
LoG
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Inverse Design for Fluid-Structure Interactions using Graph Network Simulators
Kelsey Allen, Tatiana Guevara, Kimberly Stachenfeld, Alvaro Sanchez, Peter Battaglia, Jessica Hamrick, Tobias Pfaff
NeurIPS
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Towards combinatorial invariance for Kazhdan-Lusztig polynomials
Charles Blundell, Lars Buesing, Alex Davies, Petar Veličković, Geordie Williamson *
Representation Theory
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Paper
Publication
Learning to Configure Computer Networks with Neural Algorithmic Reasoning
Luca Beurer-Kellner *, Martin Vechev *, Laurent Vanbever *, Petar Veličković
NeurIPS
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Measuring CLEVRness: Black-box Testing of Visual Reasoning Models
Spyridon Mouselinos *, Henryk Michalewski *, Mateusz Malinowski
ICLR
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Graph Neural Networks are Dynamic Programmers
Andrew Dudzik, Petar Veličković
NeurIPS
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Relating Graph Neural Networks to Structural Causal Models
Matej Zečević *, Devendra Singh Dhami *, Petar Veličković, Kristian Kersting *
arXiv
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Persistent Message Passing
Heiko Strathmann, Amin Barekatain, Charles Blundell, Petar Veličković
arXiv
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Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart *, Didier Chétalat *, Elias Khalil *, Andrea Lodi *, Christopher Morris *, Petar Veličković
IJCAI
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Paper
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Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff, Meire Fortunato, Alvaro Sanchez-Gonzalez, Peter Battaglia
arXiv
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Amortized learning of neural causal representations
N R Ke *, Jane Wang, Jovana Mitrovic, Martin Szummer, Danilo Rezende
arXiv
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Hierarchical Protein Function Prediction with Tails-GNNs
Stefan Spalević *, Petar Veličković, J Kovacević *, Mladen Nikolić *
arXiv
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Paper
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Evaluating the Apperception Engine
Richard Evans, J Hernández-Orallo *, Johannes Welbl *, Pushmeet Kohli, Marek Sergot *
arXiv
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Pointer Graph Networks
Petar Veličković, Lars Buesing, Matthew Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell
NeurIPS
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Paper
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Should I tear down this wall? Optimizing social metrics by evaluating novel actions
János Kramár, Neil Rabinowitz, Tom Eccles, Andrea Tacchetti
arXiv
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Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso *, Luca Cavalleri *, Dominique Beaini *, Pietro Liò *, Petar Veličković
NeurIPS
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Lagrangian Neural Networks
Miles Cranmer *, S Greydanus *, S Hoyer *, Peter Battaglia, David Spergel *, Shirley Ho *
arXiv
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Learning to Simulate Complex Physics with Graph Networks
Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying *, Jure Leskovec *, Peter Battaglia
ICML
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Object-oriented state editing for HRL
Victor Bapst, Alvaro Sanchez-Gonzalez, Omar Shams, Kimberly Stachenfeld, Peter Battaglia, Satinder Singh *, Jess Hamrick
NeurIPS
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