Sheffield Machine Learning Network

Next Friday, 17th June, Professor Neil Lawrence will be speaking in Sheffield on Deep Gaussian Processes: A Motivation and Introduction. The Diamond, Lecture Theatre 3. 16:30 (talk starts at 17:00). Why is uncertainty important to propagate? sheffieldmlnet.github.io 1/3

PhD position available developing and applying new methods for insect tracking, to explore and understand their behaviour. Working in a team of ML, neuroethology and ecology researchers. Apply here: findaphd.com/phds/project/u…

Sheffield computer science is now recruiting for several academic posts! sheffield.ac.uk/dcs/about/jobs

@tanujkaria @sheffielduni Thanks @tanujkaria - hope you enjoy!

The sold-out Gaussian Process Summer School has begun! Richard Wilkinson introduced GPs. Next: Carl Henrik & GP Intro 2! Thanks @wilkinson_rich @carlhenrikek! gpss.cc/gpss22/ #GPSS22

MLNet's next speaker: Professor Ivan Tyukin will be discussing his fascinating theory of learning in artificial neural networks: how it is possible to robustly achieve few-shot learning. Date: Friday, 15th July, Where: Ada Lovelace, Computer Science, Sheffield. Time: 16:00

Reminder! Neil Lawrence will be talking about Deep GPs, tomorrow (Friday) at the Diamond, in Sheffield (5pm). sheffieldmlnet.github.io

Neil previously was Professor of ML here in Sheffield. He continued to develop applied probabilistic ML while director of machine learning at Amazon in Cambridge. In 2019, he was appointed as the inaugural DeepMind Professor of Machine Learning at the University of Cambridge. 3/3

Significant advances in AI, enable super-human performance in Go and prediction of protein folding. Neil will look at deep learning from the perspective of deep Gaussian processes. These allow us to propagate uncertainty. He'll explain why this is important. 2/3

Next Friday, 17th June, Professor Neil Lawrence will be speaking in Sheffield on Deep Gaussian Processes: A Motivation and Introduction. The Diamond, Lecture Theatre 3. 16:30 (talk starts at 17:00). Why is uncertainty important to propagate? sheffieldmlnet.github.io 1/3

We are excited to announce tomorrow's neuroscience institute seminar presented by our newly appointed ML lecturer Dr. Aditya Gilra: Title: Biologically plausible learning for movement control and cognition. Date: 13th March 2020 Time: 12-1pm Venue: SITraN, B02/03

Exciting chance to be part of the ML group here in Sheffield!

Multi-fidelity Bayesian Optimisation using Max-value entropy search, inspired work by Henry Moss @Henrymossmoss. Talk at the ML Seminar.

Our next Machine Learning Seminar is by Henry Moss @Henrymossmoss, who will be talking about "MUMBO: MUlti-task Max-value Bayesian Optimization". The Seminar is on Wednesday Nov 06 at 15:00. More details in the following link sheffieldmlnet.github.io/talk/seminar-h…

Exciting posdoc opportunity for a joint post between @shefcompsci and @mathsatshefuni at Sheffield, and Kampala, tackling the challenges of monitoring air pollution from low-cost sensors.

Our next Machine Learning Seminar is by Jeremias Knoblauch (@LauchLab) on "Generalized Variational Inference". Details here: sheffieldmlnet.github.io/talk/seminar-j…

Videos and slides for the 2019 Gaussian Process and Uncertainty Quantification Summer School are now available at gpss.cc/gpss19/program

It was fun to talk about Bayesian NNs in the GP summer school in Sheffield, especially after @lawrennd criticising how crappy BNNs could be without good approximate inference

Job: two year post doc working with @maalvarezl @mikethomassmith and me in Sheffield on physically informed Gaussian processes tinyurl.com/y2eo3hho Aim is to build advection and diffusion into GP models to predict air pollution in Kampala. Closing date is 19 Sept. Please RT!

Our Machine Learning Seminar for next week will be by @Boukouva1Alexis on "Using Gaussian process models to infer pseudotime and identify gene-specific branching dynamics from single-cell data". Seminar on Friday, July 19, 14:00 hrs, Main Lewin Computer Science.

@isp_uv_es @lawrennd inverseprobability.com/talks/notes/in…

@sheffieldmlnet @lawrennd Any chance to get the slides?

A snapshot of this morning's presentations by some of the group's PhD students and affiliated members, as well as a talk by @lawrennd on end-to-end interpretable ML