Wolfson College Music Society presents Asaka Quartet



Programme -

Schubert - Quartettsatz

Beethoven - Opus 18, No. 2 in G major

Danish String Quartet - Unst Boat Song

Brahms - String Quartet No. 1 in C minor



5pm Sunday 5 May 2024



Leonard Wolfson Auditorium, Wolfson College, Linton Road, Oxford, OX2 6UD



£15 | £10 Wolfson Members | Students Free

Tickets available on the door of the event (cash only).

Celebrating Australian Music (CAM) celebrates Fauré Anniversary



6.30-7pm Talk by Dr Roy Howat, ‘Rediscovering Fauré’

7.30-8.30pm Recital of music by Fauré and Australian composers



Programme –

Wendy Hiscocks – Explorer goes East

Peter Sculthorpe – Mountains

Peggy Glanville-Hicks – Prelude to a Pensive Pupil

Gabriel Fauré – Music for cello & piano, Madrigal & Pavane



Saturday 11 May 2024



The Leonard Wolfson Auditorium, Wolfson College, Linton Road, Oxford, OX2 6UD.



Free Admission. Seats can be reserved by visiting www.celebratingaustralianmusic.com

Wolfson College Music Society presents AMREF HEALTH AFRICA CONCERT. Performed by Nima Farahmand Bafi



Programme -

Nima Farahmand Bafi - Persian fantasy

Leoš Janáček - Piano Sonata 1.X.1905

Nima Farahmand Bafi - Jin - Jiyan – Azadi (Woman – Life – Freedom)

Frédéric Chopin - Polonaise Op. 53

Nima Farahmand Bafi - Poems without words

Ernest Bloch - Nigun from Baal Shem (arr. Nima Farahmand Bafi)

Nima Farahmand Bafi - Concert paraphrase on "Chahargah" by H. Kassai



5pm Sunday 21 April 2024



Leonard Wolfson Auditorium, Wolfson College, Linton Road, Oxford, OX2 6UD



Free Admission. Donations welcome (cash only).

All donations from the concert will go to Amref Health Africa

Please join us for a fun afternoon of Easter egg activities at the Buttery from 2 - 4 pm. We will provide light snacks. Eggs and painting supplies will also be provided.



See you!

Meet the artist and join us for a final viewing of Nobuo Okawa's exhibition, From Dark to Light, An Exhibition of Mezzotint Prints on Friday 15 March 2024 from 2-6pm.



Tea and coffee will be available. A last chance to view and purchase a work from this wonderful exhibition.

Bio:

I'm currently a Research Scientist at DeepMind. I grew up in Romania and studied computer science and electrical engineering for my undergrads in Germany. I got my MSc from Jacobs University, Bremen in 2009. I hold a PhD from University of Montreal (2014), which I did under the supervision of prof. Yoshua Bengio. I was involved in developing Theano and helped writing some of the deep learning tutorials for Theano. I've published several papers on topics surrounding deep learning and deep reinforcement learning (see my scholar page). I'm one of the organizers of EEML (www.eeml.eu) and part of the organizers of AIRomania. As part of the AIRomania community, I have organized RomanianAIDays since 2020, and helped build a course on AI aimed at high school students.



Abstract:

In this talk I will focus on State Space Models (SSMs) , a subclass of Recurrent Neural Networks (RNNs) that has recently gained some attention through works like Mamba, obtaining strong performance against transformer baselines. I will start by first explaining how SSMs can be viewed as just a particular parametrization of RNNs and what are the crucial differences compared to previous recurrent architectures that led to these results. My goal is to demystify the relative complex parametrization of the architecture and identify what elements are needed for the model to perform well. In this process I will introduce the Linear Recurrent Unit (LRU), a simplified linear layer inspired by existing SSM layers. In the second part of the talk, I will focus on language modelling and the block structure in which such layers tend to be embedded. I will argue that beyond the recurrent layer itself, the block structure borrowed from transformers plays a crucial role in the recent successes of this architecture, and present results at scale of well performing hybrid recurrent architectures as compared to strong transformer baseline. I will close the talk with a few open questions and thoughts on the importance of recurrence in modern deep learning models.