Countries citing papers authored by Théophane Weber
Since
Specialization
Citations
This map shows the geographic impact of Théophane Weber's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Théophane Weber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Théophane Weber more than expected).
This network shows the impact of papers produced by Théophane Weber. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Théophane Weber. The network helps show where Théophane Weber may publish in the future.
Co-authorship network of co-authors of Théophane Weber
This figure shows the co-authorship network connecting the top 25 collaborators of Théophane Weber.
A scholar is included among the top collaborators of Théophane Weber based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Théophane Weber. Théophane Weber is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Davies, Alex, Sébastien Racanière, Grzegorz Świrszcz, et al.. (2025). Drums of high width. Proceedings of the London Mathematical Society. 130(3).
2.
Hamrick, Jessica B., Arthur Guez, Fabio Viola, et al.. (2021). On the role of planning in model-based deep reinforcement learning. arXiv (Cornell University).10 indexed citations
Guez, Arthur, Fabio Viola, Théophane Weber, et al.. (2020). Value-driven Hindsight Modelling. Neural Information Processing Systems. 33. 12499–12509.1 indexed citations
5.
Hamrick, Jessica B., Victor Bapst, Álvaro Sánchez‐González, et al.. (2020). Combining Q-Learning and Search with Amortized Value Estimates. arXiv (Cornell University).6 indexed citations
Orseau, Laurent, Levi H. S. Lelis, Tor Lattimore, & Théophane Weber. (2018). Single-Agent Policy Tree Search With Guarantees. Neural Information Processing Systems. 31. 3201–3211.3 indexed citations
8.
Buesing, Lars, Théophane Weber, Sébastien Racanière, et al.. (2018). Learning Dynamic State Abstractions for Model-Based Reinforcement Learning.1 indexed citations
9.
Racanière, Sébastien, Théophane Weber, David Reichert, et al.. (2017). Imagination-Augmented Agents for Deep Reinforcement Learning. arXiv (Cornell University). 30. 5690–5701.49 indexed citations
10.
Watters, Nicholas, Daniel Zoran, Théophane Weber, et al.. (2017). Visual Interaction Networks: Learning a Physics Simulator from Video. Neural Information Processing Systems. 30. 4539–4547.74 indexed citations
11.
Eslami, S. M. Ali, Nicolas Heess, Théophane Weber, et al.. (2016). Attend, infer, repeat: fast scene understanding with generative models. 29. 3233–3241.31 indexed citations
Gamarnik, David, David A. Goldberg, & Théophane Weber. (2013). Correlation Decay in Random Decision Networks. Mathematics of Operations Research. 39(2). 229–261.10 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.