Tom Silver

727 total citations
22 papers, 226 citations indexed

About

Tom Silver is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Infectious Diseases. According to data from OpenAlex, Tom Silver has authored 22 papers receiving a total of 226 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Infectious Diseases. Recurrent topics in Tom Silver's work include AI-based Problem Solving and Planning (13 papers), Reinforcement Learning in Robotics (7 papers) and Machine Learning and Algorithms (6 papers). Tom Silver is often cited by papers focused on AI-based Problem Solving and Planning (13 papers), Reinforcement Learning in Robotics (7 papers) and Machine Learning and Algorithms (6 papers). Tom Silver collaborates with scholars based in United States. Tom Silver's co-authors include Leslie Pack Kaelbling, Joshua B. Tenenbaum, Tomás Lozano‐Pérez, Rohan Chitnis, Andrés Colubri, Ben Fry, Pardis C. Sabeti, Josh Tenenbaum, Kelsey R. Allen and Kavitha Srinivas and has published in prestigious journals such as Cognitive Science, PLoS neglected tropical diseases and arXiv (Cornell University).

In The Last Decade

Tom Silver

18 papers receiving 205 citations

Peers

Tom Silver

CVPR

CSE

RNMI

Roberto Capobianco Italy

Paul Duckworth United Kingdom

Yazhou Yang China

Khalid Shaker Iraq

Himanshu Buckchash India

Arpan Basu India

Sandra Ebert Germany

Elliot Meyerson United States

Yongbin Li China

Zheming Zuo United Kingdom

Roberto Capobianco Italy

Tom Silver

82 ×0.6

72 ×1.1

CVPR

26 ×0.5

CSE

7 ×0.4

RNMI

7 ×0.4

Citations per year, relative to Tom Silver Tom Silver (= 1×) peers Roberto Capobianco

Countries citing papers authored by Tom Silver

Since Specialization

Citations

This map shows the geographic impact of Tom Silver'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 Tom Silver with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Silver more than expected).

Fields of papers citing papers by Tom Silver

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Silver. 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 Tom Silver. The network helps show where Tom Silver may publish in the future.

Co-authorship network of co-authors of Tom Silver

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Silver. A scholar is included among the top collaborators of Tom Silver 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 Tom Silver. Tom Silver is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Silver, Tom, et al.. (2025). GRACE: Generalizing Robot-Assisted Caregiving with User Functionality Embeddings. 686–695. 1 indexed citations

Silver, Tom, et al.. (2025). FEAST: A Flexible Mealtime-Assistance System Towards In-the-Wild Personalization. 1 indexed citations

Silver, Tom, et al.. (2024). Practice Makes Perfect: Planning to Learning Skill Parameter Policies. 3 indexed citations

Silver, Tom, et al.. (2024). Generalized Planning in PDDL Domains with Pretrained Large Language Models. Proceedings of the AAAI Conference on Artificial Intelligence. 38(18). 20256–20264. 27 indexed citations

Silver, Tom, et al.. (2023). Predicate Invention for Bilevel Planning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(10). 12120–12129. 10 indexed citations

Chitnis, Rohan, et al.. (2022). Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators. Proceedings of the International Conference on Automated Planning and Scheduling. 32. 588–596. 10 indexed citations

Silver, Tom, et al.. (2022). PG3: Policy-Guided Planning for Generalized Policy Generation. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 4686–4692. 1 indexed citations

Silver, Tom, et al.. (2022). Discovering State and Action Abstractions for Generalized Task and Motion Planning. Proceedings of the AAAI Conference on Artificial Intelligence. 36(5). 5377–5384. 7 indexed citations

Chitnis, Rohan, Tom Silver, Joshua B. Tenenbaum, Leslie Pack Kaelbling, & Tomás Lozano‐Pérez. (2021). GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling. Proceedings of the AAAI Conference on Artificial Intelligence. 35(13). 11782–11791. 6 indexed citations

10.

Zhi‐Xuan, Tan, et al.. (2020). Online Bayesian Goal Inference for Boundedly Rational Planning Agents. Neural Information Processing Systems. 33. 19238–19250. 1 indexed citations

11.

Silver, Tom, et al.. (2020). Few-Shot Bayesian Imitation Learning with Logical Program Policies. Proceedings of the AAAI Conference on Artificial Intelligence. 34(6). 10251–10258. 14 indexed citations

12.

Chitnis, Rohan, Tom Silver, Joshua B. Tenenbaum, Leslie Pack Kaelbling, & Tomás Lozano‐Pérez. (2020). GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling. arXiv (Cornell University). 35(13). 11782–11791. 1 indexed citations

13.

Allen, Kelsey R., et al.. (2020). Learning constraint-based planning models from demonstrations. 5410–5416. 8 indexed citations

14.

Silver, Tom, et al.. (2020). Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks. arXiv (Cornell University). 35(13). 11962–11971. 1 indexed citations

15.

Chitnis, Rohan, Tom Silver, Joshua B. Tenenbaum, Leslie Pack Kaelbling, & Tomás Lozano‐Pérez. (2020). GLIB: Exploration via Goal-Literal Babbling for Lifted Operator Learning. 1 indexed citations

16.

Silver, Tom, et al.. (2019). Few-Shot Bayesian Imitation Learning with Logic over Programs.. arXiv (Cornell University). 4 indexed citations

17.

Silver, Tom, et al.. (2019). Discovering a symbolic planning language from continuous experience.. Cognitive Science. 2193. 1 indexed citations

18.

Stark, Michael, Alexander Schlegel, Carter Wendelken, et al.. (2018). Behavior Is Everything: Towards Representing Concepts with Sensorimotor Contingencies. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 12 indexed citations

19.

Silver, Tom, et al.. (2017). Schema networks: zero-shot transfer with a generative causal model of intuitive physics. International Conference on Machine Learning. 1809–1818. 8 indexed citations

20.

Colubri, Andrés, et al.. (2016). Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients. PLoS neglected tropical diseases. 10(3). e0004549–e0004549. 56 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.

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