Edward Grefenstette is affiliated with University College London in the United Kingdom and primarily works in the field of Computer Science, focusing on Artificial Intelligence. Their published work spans several subfields including Computer Science Applications, Management Science and Operations Research, Computer Vision and Pattern Recognition, and General Health Professions.
Their main research topics highlight areas such as Reinforcement Learning in Robotics, Topic Modeling, Adversarial Robustness in Machine Learning, Natural Language Processing Techniques, Data Stream Mining Techniques, Explainable Artificial Intelligence (XAI), and Advanced Graph Neural Networks.
Frequent co-authors collaborating with Edward Grefenstette include:
Their research has been published mainly in venues such as:
Selected recent publications include:
Nal Kalchbrenner;Edward Grefenstette;Phil Blunsom
Karl Moritz Hermann;Tomáš Kočiský;Edward Grefenstette;Lasse Espeholt
Alex Graves;Greg Wayne;Malcolm Reynolds;Tim Harley
Tim Rocktäschel;Edward Grefenstette;Karl Moritz Hermann;Tomáš Ko iský;Tomáš Ko iský
Tim Rocktäschel;Edward Grefenstette;Karl Moritz Hermann;Tomáš Kočiský
Tomáš Kočiský;Jonathan Schwarz;Phil Blunsom;Chris Dyer
Richard Evans;Edward Grefenstette
Wang Ling;Phil Blunsom;Edward Grefenstette;Karl Moritz Hermann
Edward Grefenstette;Mehrnoosh Sadrzadeh
Edward Grefenstette;Karl Moritz Hermann;Mustafa Suleyman;Phil Blunsom
Yishu Miao;Edward Grefenstette;Phil Blunsom
Jelena Luketina;Nantas Nardelli;Nantas Nardelli;Gregory Farquhar;Gregory Farquhar;Jakob N. Foerster
Wang Ling;Edward Grefenstette;Karl Moritz Hermann;Tomáš Kočiský
David Saxton;Edward Grefenstette;Felix Hill;Pushmeet Kohli
Unknown
Dani Yogatama;Phil Blunsom;Chris Dyer;Edward Grefenstette
E. Grefenstette;G. Dinu;Y. Zhang;M. Sadrzadeh
Edward Grefenstette;Brandon Amos;Denis Yarats;Phu Mon Htut
Dzmitry Bahdanau;Felix Hill;Jan Leike;Edward Hughes
Bob Coecke;Edward Grefenstette;Mehrnoosh Sadrzadeh
Richard Evans;David Saxton;David Amos;Pushmeet Kohli
Heinrich Küttler;Nantas Nardelli;Alexander H. Miller;Roberta Raileanu
Richard Evans;Edward Grefenstette
If you think any of the details on this page are incorrect, let us know.
If you’re considering studying Computer Science in the USA, it’s helpful to explore related online degrees and career pathways. Many students pair Computer Science with fields like mechanical engineering, data science, and electrical engineering to enhance their career prospects and develop a broad tech skill set.
One key factor for students is the mechanical engineering cost of education, which can influence your decision between different STEM pathways. For those interested in physics, finding the cheapest online physics degree is also a popular concern, especially if budget is a priority.
Data science is another closely related field, and choosing a data science degree from an affordable program can open doors in sectors like business, healthcare, and AI. Additionally, if you are curious about electrical engineering, seeking out accredited online electrical engineering programs ensures you receive quality education recognized by employers.
These flexible online options allow you to shape your educational journey to match your interests, budget, and career goals—all from wherever you are.
University of Newcastle Australia
University of Akron
Cornell University
Federal University of Campina Grande
Italian Institute of Technology
Norwegian University of Science and Technology
University of Orléans
University of Copenhagen
Texas Woman's University
Vanderbilt University
Elemental Cognition
Nokia (United States)
Imperial College London
Philipp University of Marburg
Serbian Academy of Sciences and Arts
University of Western Ontario
