A Review of Machine Learning Techniques for Anomaly Detection - Dr. David Green
Explore machine learning techniques for anomaly detection, covering traditional methods, deep neural networks, and practical applications in various domains.
Detecting Semantic Shift in Large Corpora by Exploiting Temporal Random Indexing
Explore semantic shift in large corpora using Temporal Random Indexing. Learn to analyze word meaning evolution over time and see applications in Italian and UK internet archive corpus analysis.
Breaking the Curse of Dimension in Quantum Mechanical Computations Through Analysis and Probability
Explore quantum mechanical computations, focusing on breaking dimensional constraints through analysis and probability. Learn about density functional theory and recent approaches to tackle existing issues.
Parsimonious Representations in Data Science - Dr. Armin Eftekhari, University of Edinburgh
Explore geometric structures in data, from linear subspace models to nonlinear approaches, for efficient data analysis and representation in the era of big data.
Time Series Class - Part 1 - Dr Ioannis Papastathopoulos, University of Edinburgh
Learn fundamental concepts and advanced techniques for analyzing time series data, including ARMA models, state-space models, and neural networks for forecasting and inference.
Time Series Class - Part 1 - Dr. Ioannis Papastathopoulos, University of Edinburgh
Learn fundamental concepts and advanced techniques in time series analysis, including ARMA models, state-space models, and neural networks for forecasting and inference.
Time Series Class - Part 2 - Professor Chris Williams, University of Edinburgh
Explore time series analysis, from moving average models to advanced state-space techniques and recurrent neural networks. Gain practical skills in parameter estimation, forecasting, and applying models to real-world data.
Reinforcement and Mean-Field Games in Algorithmic Trading - Sebastian Jaimungal
Explore reinforcement learning and mean-field games in algorithmic trading, covering deep Q-learning, reinforced deep Kalman filters, and heterogeneous agent interactions with differing beliefs in financial markets.
Explaining Generalisation and Individual Justice - Reuben Binns
Explore the challenges of balancing generalization and individual justice in AI decision-making, focusing on explainability, limitations, and ethical implications in real-world contexts.
Nonlinear Approximation by Deep ReLU Networks - Ron DeVore, Texas A&M
Explores deep ReLU networks for nonlinear approximation, covering architecture, error analysis, and manifold approximation. Bridges mathematics, statistics, and computer science in data science applications.
From Shallow to Deep Learning for Inverse Imaging Problems - Carola-Bibiane Schönlieb, Cambridge
Explore deep learning for inverse imaging problems, covering regularization techniques, neural networks, and optimization strategies for improved image reconstruction and analysis.
Is There a Post-Pandemic AI Panacea
Exploring AI's limited impact on pandemic response, challenges in health data science, and lessons from COVID-19. Experts discuss AI strengths, weaknesses, and future potential in healthcare.
Modelling and Predicting Climate Change
Explore innovative methods for monitoring and predicting climate change, from Antarctic sea ice to forest ecosystems, with leading environmental scientists using AI and data science.
TMCF Workshop Use-Cases - Counterfactual CPMS & Emerging COVID Work, Niels Peek
Exploring causal inference in AI prediction algorithms for decision-making, focusing on 'what if' scenarios in healthcare and insurance, with applications to COVID-19 pandemic response.
AIUK 2022 Workshop - RADDISH: Real-Time Data Assimilation for Digital Twins
Explore real-time data assimilation for digital twins using particle filtering techniques, with interactive demonstrations and discussions on parallelization, future applications, and implementation challenges.
Preserving Patient Safety as AI Transforms Clinical Care - Curt Langlotz, Stanford University
Explore AI's impact on healthcare, focusing on patient safety, data privacy, and interpretability. Learn about new machine learning methods supporting caregivers and enhancing clinical decision-making.
MOSIP Research Platform - Integrating Anomaly Detection Prototypes into Centralized ID Systems
Explore novel anomaly detection methods for digital identity systems using autoencoders, with a focus on fraud prevention during registration in MOSIP architecture.
Towards Creating Time Sensitive Sensors from User-Generated Language and Heterogeneous Content
Exploring the creation of time-sensitive sensors using user-generated language and diverse content to advance natural language processing and its real-world applications.
Probabilistic Methods for Increased Robustness in Machine Learning
Explore probabilistic methods to enhance machine learning robustness, focusing on latent variables, molecular design, and optimization techniques for improved AI performance and reliability.
Preprocessing Revisited
Explore new developments in chemometric preprocessing, including multi-block strategies and Variable Sorting for Normalization, to reduce unwanted variability in experimental data.
The 10 Equations That Rule the World - With David Sumpter
Explore 10 key mathematical equations and their real-world applications in finance, relationships, social media, and personal development with Professor David Sumpter.