Tiago Ramalho

9 papers receiving 4.2k citations

Hit Papers

Overcoming catastrophic forgetting in neural networks20162026201920222017201610002.0k3.0k

Peers

Tiago Ramalho
Comparison fields: 5 of 150
  • Artificial Intelligence 3.1k
  • Computer Vision and Pattern Recognition 1.6k
  • Electrical and Electronic Engineering 423
  • Cognitive Neuroscience 294
  • Radiology, Nuclear Medicine and Imaging 250
Replace Agnieszka Grabska‐Barwińska with:
Agnieszka Grabska‐Barwińska United Kingdom
John Quan United States
Kieran Milan India
Guillaume Desjardins Canada
Neil C. Rabinowitz United Kingdom
Rich Zemel Canada
Mario Fritz Germany
Barbara Hammer Germany
Jason Yosinski United States
Lei Li China
Tiago Ramalho relative to Agnieszka Grabska‐Barwińska United Kingdom Agnieszka Grabska‐Barwińska's profile →
Citations per field
00.5×1.5×
Agnieszka Grabska‐Barwińska · 1×
Citations per year

Countries citing papers authored by Tiago Ramalho

Since Specialization
Citations

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

Fields of papers citing papers by Tiago Ramalho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tiago Ramalho

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

All Works

9 of 9 papers shown
#WorkIndexed citations
1 2
2 2
3
Learning to encode spatial relations from natural language
2
4
Overcoming catastrophic forgetting in neural networksbreakdown →
3594
5 17
6
Hybrid computing using a neural network with dynamic external memorybreakdown →
683
7 11
8 48
9 6

About Tiago Ramalho

Tiago Ramalho is a scholar working on Endocrinology, Geography, Planning and Development and Biophysics, having authored 9 papers that have together received 4.4k indexed citations. Recurring topics across this work include Neural Networks and Applications (2 papers), Bacterial Genetics and Biotechnology (2 papers) and Gene Regulatory Network Analysis (2 papers). The work is most often cited by research in Artificial Intelligence (3.1k citations), Computer Vision and Pattern Recognition (1.6k citations) and Health Informatics (40 citations). Tiago Ramalho has collaborated with scholars based in Germany, United Kingdom and Netherlands. Frequent co-authors include Agnieszka Grabska‐Barwińska, Demis Hassabis, Kieran Milan, James Kirkpatrick, Neil C. Rabinowitz, Dharshan Kumaran, Raia Hadsell, Guillaume Desjardins, John Quan and Andrei A. Rusu. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and PLoS ONE.

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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