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.

Category: Uncategorised

Yoshua Wuyts from Microsoft will give a talk, in person and online, for the Coffee House Tech Talk Series. Details of the talk are below. Title: Introducing Effect Types to the Rust Programming Language Speaker: Yoshua Wuyts                     Microsoft When: 11am Tue 30 April Where: Meeting […]

Melissa Terras from the University of Edinburgh will give a talk, in person and online, for the Coffee House Tech Talk Series. Details of the talk are below. Title: Creative Informatics: Catalysing Edinburgh’s Creative Community to Innovate with Data Speaker: Melissa Terras                      University of Edinburgh […]

Nick Wu will give a talk, in person and online, for the Coffee House Tech Talk Series.  The details of the talk are below. A lunch will be provided after the talk.   Title: Modular Models of Monoids with Operations When : 28 Mar 2023, 11am-12nn Where (Physically) : Coffee House, 4/F, Bayes Centre, 47 […]

Date Thursday 27th October @ 14:00 – 15:00 (UK time) Presenter Prof. Haris Volos Affiliation University of Cyprus Location Bayes center G.03 Online link: TBD Note: this is a talk open to the public. Abstract Persistent memory has emerged as a key persistence programming model for non-volatile memory technologies, such as Intel Optane Persistent Memory. […]

by Beniamino Accattoli (INRIA) and Giulio Guerrieri (Huawei Edinburgh, PL team) The denotational semantics of the untyped lambda-calculus is a well developed field built around the concept of solvable terms, which are elegantly characterized in many different ways. In particular, unsolvable terms provide a consistent notion of meaningless term. The semantics of the untyped call-by-value […]

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 […]

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 […]

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.  

Professor Prakash Panangaden will review the concept of probabilistic bisimulation and its extension to systems with continuous state spaces.  Surprisingly, it turned out that one can prove a striking logical characterization theorem: a theorem that pins down exactly what differences one can ‘’see’’ in process behaviours when two systems are not bisimilar.  I will outline […]

Abstract:Lua is a scripting language widely uses in several fields, with strong niches in games and embedded systems. Pallene is a new language designed to be a companion language for Lua, that is, a system language specifically designed to interoperate with Lua in a scripting architecture.In this talk, Roberto will present the main features of […]

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