Any views expressed within media held on this service are those of the contributors, should not be taken as approved or endorsed by the University, and do not necessarily reflect the views of the University in respect of any particular issue.

Date Thursday 9 June @ 09:30 – 10:30 (UK time) Presenter Maciej Besta Affiliation ETH Zurich Location [Online] Meeting link: https://welink.zhumu.com/j/158022218   Abstract Graph neural networks (GNNs) are among the most powerful tools in deep learning. They routinely solve complex problems on unstructured networks, such as node classification, graph classification, or link prediction, with high […]

Dr. Dominic Orchard (University of Kent) will give a talk, in person and online, for the Coffee House Tech Talk Series. The details of the talk are below. When: Tuesday 31 May 2022 at 11am (UK time). Where (in person): Room G.03, Bayes Centre (47 Potterrow, Edinburgh EH8 9BT). Where (virtually): Zhumu link (https://meeting.zhumu.me/wc/0178099193/join?track_id=&jmf_code=&meeting_result=&tk=&cap=d7cec&prefer=0), everybody […]

Bcc to all staff of UKRD ——————– When: Tuesday 17 May 2022 at 11am (UK time). Where (in person): Room G.03, Bayes Centre (47 Potterrow, Edinburgh EH8 9BT). Where (virtually): Zhumu link (https://meeting.zhumu.me/wc/0145848734/join?track_id=&jmf_code=&meeting_result=&tk=&cap=d7cec&prefer=0), everybody is welcome! You can access it from your own browser or Zoom app, without installing anything. Speaker: Paul B. Levy (University of Birmingham)

When: Tuesday 24 May 2022 at 11am (UK time). Where (in person): Room G.03, Bayes Centre (47 Potterrow, Edinburgh EH8 9BT). Where (virtually): Zhumu link: http://imeeting.huawei.com/meeting/join?id=0148144957&app=welink&sectype=0 Speakers: Nobuko Yoshida and Martin Vassor (Imperial College London)

Date Tuesday 17 May @ 09:30 – 10:30 (UK time) Presenter Christina Giannoula Affiliation National Technical University of Athens (NTUA) Location [Online] Meeting link: https://welink.zhumu.com/j/149868852   Abstract Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures, after decades of research efforts. Near-bank PIM architectures place simple cores close to DRAM banks. Recent research […]

Link: https://meeting.zhumu.me/wc/join/0179880767?tk=&prefer=0&track_id=&meeting_result=&jmf_code=&wpk=   

Xavier Denis (University of Paris-Saclay, France) will give an talk, in person and online, for the Huawei – Edinburgh Coffee House Tech Talk Series. The details of the talk are below. *When*: Tuesday 26 April 2022 at 11am *Where* (in person): Huawei Edinburgh Research Centre (2 Semple Street, 5th floor, Meeting Room 1, Edinburgh EH3 […]

Taming Large Intermediate Results for Joins over Graph-Structured Relations Date: 26th April 2022 Time: 14:00 – 15:30 Location: Virtual   Abstract: Querying graph-structured relations, i.e., those with many-to-many (m-n) relationships between entities, is ubiquitous and integral to a wide range of analytical applications such as recommendations on social networks and fraud detection in financial transactional […]

Time:2022-03-29 11:00 — 12:00 Location:Edinburgh Coffee House Speaker:Dr. Ian Mackie (University of Sussex) Overview ▶ Very simple GOI for System T. ▶ Reversible machinery for higher-order language. ▶ Depending on how we constrain the use of the recursor, this language is rich enough to capture all primitive recursive functions or more generally Gödel’s System T. […]

The recording of “Prof Prakash Panangaden’s talk on Probabilistic Bisimulation and associated metrics” is now available using the link below:   https://ed-ac-uk.zoom.us/rec/share/mwX23U03YMrWZrTgEKl-jMbyAAdUnUULxBa32XnyFcDI9XkHPY54FSELDsnm9xI7.-Hb0fb6YP-bWqgTH   Professor Panangaden is conducting joint research in Edinburgh supported by the Huawei – University of Edinburgh Strategic Talent Programme.  

css.php

Report this page

To report inappropriate content on this page, please use the form below. Upon receiving your report, we will be in touch as per the Take Down Policy of the service.

Please note that personal data collected through this form is used and stored for the purposes of processing this report and communication with you.

If you are unable to report a concern about content via this form please contact the Service Owner.

Please enter an email address you wish to be contacted on. Please describe the unacceptable content in sufficient detail to allow us to locate it, and why you consider it to be unacceptable.
By submitting this report, you accept that it is accurate and that fraudulent or nuisance complaints may result in action by the University.

  Cancel