Edward Grefenstette
- Artificial Intelligence top 0.2%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 1%
- Electrical and Electronic Engineering
- Signal Processing top 5%
- Co-authors
- Phil BlunsomNal KalchbrennerMehrnoosh SadrzadehKarl Moritz HermannJohn AgapiouMalcolm ReynoldsTim HarleyAdrià Puigdomènech Badia
- Topics
- Natural Language Processing Techniques (18 papers)Topic Modeling (17 papers)Reinforcement Learning in Robotics (6 papers)
- Partner nations
- United KingdomUnited StatesIsrael
In The Last Decade
Edward Grefenstette
33 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Artificial Intelligence 2.8k
- Computer Vision and Pattern Recognition 616
- Information Systems 510
- Electrical and Electronic Engineering 235
- Signal Processing 172
Countries citing papers authored by Edward Grefenstette
This map shows the geographic impact of Edward Grefenstette'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 Edward Grefenstette with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward Grefenstette more than expected).
Fields of papers citing papers by Edward Grefenstette
This network shows the impact of papers produced by Edward Grefenstette. 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 Edward Grefenstette. The network helps show where Edward Grefenstette may publish in the future.
Co-authorship network of co-authors of Edward Grefenstette
This figure shows the co-authorship network connecting the top 25 collaborators of Edward Grefenstette. A scholar is included among the top collaborators of Edward Grefenstette 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 Edward Grefenstette. Edward Grefenstette is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 75 | |
| 2 | 8 | |
| 3 | Learning with AMIGo: Adversarially Motivated Intrinsic Goals | 1 |
| 4 | RTFM: Generalising to New Environment Dynamics via Reading | 4 |
| 5 | The NetHack Learning Environment | 2 |
| 6 | Learning to Follow Language Instructions with Adversarial Reward Induction | 4 |
| 7 | Jointly Learning "What" and "How" from Instructions and Goal-States. | 2 |
| 8 | 5 | |
| 9 | Discovering Discrete Latent Topics with Neural Variational Inference | 51 |
| 10 | 176 | |
| 11 | Hybrid computing using a neural network with dynamic external memorybreakdown → | 683 |
| 12 | 18 | |
| 13 | A Convolutional Neural Network for Modelling Sentencesbreakdown → | 2216 |
| 14 | 28 | |
| 15 | 12 | |
| 16 | 34 | |
| 17 | A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations | 1 |
| 18 | 30 | |
| 19 | 133 | |
| 20 | Analysing Document Similarity Measures | 4 |
About Edward Grefenstette
Edward Grefenstette is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 33 papers that have together received 3.7k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (18 papers), Topic Modeling (17 papers) and Reinforcement Learning in Robotics (6 papers). The work is most often cited by research in Artificial Intelligence (2.8k citations), Computer Vision and Pattern Recognition (616 citations) and Information Systems (510 citations). Edward Grefenstette has collaborated with scholars based in United Kingdom, United States and Israel. Frequent co-authors include Phil Blunsom, Nal Kalchbrenner, Mehrnoosh Sadrzadeh, Karl Moritz Hermann, Phil Blunsom, John Agapiou, Malcolm Reynolds, Tim Harley, Adrià Puigdomènech Badia and Yori Zwólš. Their work appears in journals such as Nature, Computational Linguistics and Lecture notes in computer science.
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.