We demonstrate the first application of deep reinforcement learning to autonomous driving. From randomly initialised parameters, our model is able learn a policy for lane following in handful training episodes using single monocular image as input. provide general and easy obtain reward: distance travelled by vehicle without safety driver taking control. use continuous, model-free algorithm, with all exploration optimisation performed on-vehicle. This demonstrates new framework driving which...

Recurrent neural networks (RNNs) are notoriously difficult to train. When the eigenvalues of hidden weight matrix deviate from absolute value 1, optimization becomes due well studied issue vanishing and exploding gradients, especially when trying learn long-term dependencies. To circumvent this problem, we propose a new architecture that learns unitary matrix, with exactly 1. The challenge address is parametrizing matrices in way does not require expensive computations (such as...

Adrian Weller acknowledges support by the Alan Turing Institute under EPSRC grant EP/N510129/1, and Leverhulme Trust via CFI.

Many people share their activities with others through online communities. These shared have an impact on other users' activities. For example, users are likely to become interested in items that adopted (e.g. liked, bought and shared) by friends. In this paper, we propose a probabilistic model for discovering latent influence from sequences of item adoption events. An inhomogeneous Poisson process is used modeling sequence, which user triggers the subsequent same users. multiple items,...

Hand-crafting generalised decision-making rules for real-world urban autonomous driving is hard. Alternatively, learning behaviour from easy-to-collect human demonstrations appealing. Prior work has studied imitation (IL) with a number of limitations. Examples include only performing lane-following rather than following user-defined route, using single camera view or heavily cropped frames lacking state observability, lateral (steering) control, but not longitudinal (speed) control and lack...

What you need to know• Both qualitative and quantitative data are critical for evaluating guiding improvement• A family of measures, incorporating outcome, process, balancing should be used track improvement work• Time series analysis, using small amounts collected displayed frequently, is the gold standard improvementWe all a way understand quality care we providing, or receiving, how our service performing.We use range in order fulfil this need, both qualitative.Data defined as...

We investigate the Student-t process as an alternative to Gaussian a nonparametric prior over functions. derive closed form expressions for marginal likelihood and predictive distribution of process, by integrating away inverse Wishart covariance kernel model. show surprising equivalences between different hierarchical models leading processes, new sampling scheme which helps elucidate these equivalences. Overall, we that can retain attractive properties -- representation, analytic...

We develop parallel predictive entropy search (PPES), a novel algorithm for Bayesian optimization of expensive black-box objective functions. At each iteration, PPES aims to select batch points which will maximize the information gain about global maximizer objective. Well known strategies exist suggesting single evaluation point based on previous observations, while far fewer are selecting batches evaluate in parallel. The few selection schemes that have been studied all resort greedy...

<h3>ABSTRACT</h3> There is increasing interest and belief in applying quality improvement (QI) to help solve our most complex challenges healthcare, yet little published literature leaders develop a business case evaluate return on investment from QI. This even more pronounced fields such as mental health community services. paper presents framework identify, understand large-scale application of QI healthcare providers. The has been developed at East London NHS Foundation Trust (ELFT),...

Violence is the biggest cause of reported safety incidents at East London NHS Foundation Trust. Evidence suggests utility structured risk assessment, discussion violence in ward community meetings and use restraint seclusion psychiatric wards. The Tower Hamlets Reduction Collaborative brought together six wards with aim reducing by 40% end 2015. A collaborative learning system was used to test a bundle four interventions on acute admissions two intensive care units. reduction physical seen...

### What you need to know In recent years we have seen a proliferation in the interest and use of quality improvement health healthcare. This represents promising shift our mental models about how solve some most complex issues. Alongside increasing word “improvement” everyday language within healthcare, there are differences understanding what exactly mean by term “quality improvement.” article explores difference between management system, defining describing best alongside control,...

Quality iMproveMent

Algebraic data types (ADTs) are a construct classically found in functional programming languages that capture structures like enumerated types, lists, and trees. In recent years, interest ADTs has increased. For example, popular languages, Python, have added support for ADTs. Automated reasoning about can be done using satisfiability modulo theories (SMT) solving, an extension of the Boolean problem with first-order logic associated background theories. Unfortunately, SMT solvers do not...

Against a backdrop of stalling life expectancy, the COVID-19 pandemic highlighted need to tackle inequities in healthcare. Quality improvement has become an increasingly recognised way tackling complex problems This article presents step-by-step approach for use quality pursue equity at NHS provider England. The Model Improvement was used set aim, develop theory change and measures, test ideas through plan-do-study-act cycles. A five-step sequence provide structured identifying problems....

The healthcare industry is a major contributor to climate change globally. There growing interest in using quality improvement methods improve the sustainability of healthcare. East London NHS Foundation Trust uses as its approach solving complex problems. This article case study methodology describe how trust's programme used at both systemic and local levels support organisation reduce direct greenhouse gas emissions by 40% 2025 indirect 2036. Using structured way enabled staff service...

Quality improvement is increasingly being used within healthcare as an operating model to empower and enable teams of staff service users at the point care find solutions complex quality safety issues. Adopting methods in poses several challenges, many providers have faced barriers embedding a culture that nurtures supports systematic approach problem-solving care. This article proposes simple framework with three components help systems avoid common introducing interventions. First,...

In 2021, 38 healthcare teams across England and Wales took part in the national enjoying work quality improvement collaborative, which aimed to enhance staff wellbeing create joy work. Participating were supported use methodology tools as of a learning network. At end programme, 16 saw an at least one outcome measure, while 17 sustained deterioration measure. Aggregate data from all demonstrated improvements baseline three measures, with 51% average percentage people who frequently enjoyed...

The East London National Health Service Foundation Trust (ELFT) Community Musculoskeletal (MSK) Physiotherapy had reported a high rate of non-attendance at scheduled appointments. This was leading to delayed access treatment for patients and reduced capacity service users, as well waste clinical resources. aim this quality improvement project therefore reduce the percentage missed appointments within department. study undertaken by ELFT community MSK service, with support from Quality...