2026/27 Undergraduate Module Catalogue

SOEE2055 Inverse Theory

10 Credits Class Size: 35

Module manager: Chris Davies
Email: C.Davies@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2026/27

Pre-requisite qualifications

Students must have prior knowledge of linear algebra.

Co-requisites

SOEE2041 Advanced Mathematics 3

Module replaces

SOEE3250, SOEE5675M

This module is not approved as a discovery module

Objectives

On completion of this module, students should be able to ...
Provide an understanding of making inferences about the Earth or the atmosphere from indirect observations based on both linear and nonlinear models. To provide an understanding of how to quantify the uncertainty of these inferences, based on data uncertainty and model setup.

Lectures will provide theoretical foundations for the different approaches, which will be implemented in the weekly practicals.

Learning outcomes

After completing this module, students will have demonstrated the following learning outcomes:

SSLO1: Formulate and parameterise inverse problems while appreciating and quantifying uncertainty in inverse problems
SSLO2: Solve linear inverse problems using least-squares or linearise and solve non-linear inverse problems
SSLO3: Apply regularisation methods for ill-posed problems
SSLO4: Formulate and solve inverse problems in terms of probability distributions, and appreciate the link between inverse theory and machine learning

Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills learning outcomes:

SKLO1: Develop analytical skills to implement algorithms and visualise data sets (Digital Skills: Digital proficiency & productivity)
SKLO2: Problem-solve using computer code (Digital Skills: Digital creation, problem solving and innovation)
SKLO3: Summarise findings in concise scientific reports including the effective use of graphs and figures (Academic Skills: Academic writing)
SKLO4: Develop the ability to plan time and working to deadlines (Work Ready Skills: Time management, planning & organising)

Teaching Methods

Delivery type Number Length hours Student hours
Lectures 10 1 10
Practicals 10 2 20
Private study hours 70
Total Contact hours 30
Total hours (100hr per 10 credits) 100

Opportunities for Formative Feedback

Students will receive formative feedback from both the module leader and demonstrators at the weekly practicals.

Methods of Assessment

Coursework
Assessment type Notes % of formal assessment
Coursework Coursework 20
Total percentage (Assessment Coursework) 20

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams
Exam type Exam duration % of formal assessment
Standard exam (closed essays, MCQs etc) (S1) 1.0 Hrs 30 Mins 80
Total percentage (Assessment Exams) 80

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading List

Check the module area in Minerva for your reading list

Last updated: 30/04/2026

Errors, omissions, failed links etc should be notified to the Catalogue Team