Category: Data Science

Uncertainty Quantification

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Explainability & Interpretability

Uncertainty quantification is the process of identifying and measuring the unknowns in a system or model. It helps people understand how confident they can be in predictions or results by showing the possible range of outcomes and where things might go wrong. This is important in fields like engineering, science, and finance, where decisions are…

Robust Feature Learning

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Embeddings & Representations

Robust feature learning is a process in machine learning where models are trained to identify and use important patterns or characteristics in data, even when the data is noisy or contains errors. This means the features the model relies on will still work well if the data changes slightly or if there are unexpected variations….

Causal Effect Variational Autoencoders

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Deep Learning

Causal Effect Variational Autoencoders are a type of machine learning model designed to learn not just patterns in data, but also the underlying causes and effects. By combining ideas from causal inference and variational autoencoders, these models aim to separate factors that truly cause changes in outcomes from those that are just correlated. This helps…

Knowledge Consolidation

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Model Training & Tuning

Knowledge consolidation is the process by which information learned or acquired is stabilised and stored in long-term memory. This process helps new knowledge become more permanent, making it easier to recall and use later. It often involves revisiting, reviewing, or practising information over time to strengthen understanding and retention.

Bayesian Optimisation

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Model Optimisation Techniques

Bayesian Optimisation is a method for finding the best solution to a problem when evaluating each possible option is expensive or time-consuming. It works by building a model of the problem and using it to predict which options are most promising to try next. This approach is especially useful when you have limited resources or…

Symbolic Regression

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Model Training & Tuning

Symbolic regression is a type of machine learning that tries to find mathematical equations that best fit a set of data. Instead of just adjusting numbers in a fixed equation, symbolic regression searches for both the structure and the parameters of equations. This means it can suggest entirely new formulas that describe how inputs relate…

Temporal Graph Networks

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Graph-Based Learning

Temporal Graph Networks are a type of machine learning model that analyse data where relationships between items change over time. These models track not only the connections between objects, like people or devices, but also how these connections appear, disappear, or change as time passes. This helps to understand patterns and predict future events in…

Spectral Graph Theory

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Graph-Based Learning

Spectral graph theory studies the properties of graphs using the mathematics of matrices and their eigenvalues. It looks at how the structure of a network is reflected in the numbers that come from its adjacency or Laplacian matrices. This approach helps to reveal patterns, connections, and clusters within networks that might not be obvious at…

Curiosity-Driven Exploration

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Reinforcement Learning Systems

Curiosity-driven exploration is a method where a person or a computer system actively seeks out new things to learn or experience, guided by what seems interesting or unfamiliar. Instead of following strict instructions or rewards, the focus is on exploring unknown areas or ideas out of curiosity. This approach is often used in artificial intelligence…

Structured Prediction

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Data Science, Model Training & Tuning

Structured prediction is a type of machine learning where the goal is to predict complex outputs that have internal structure, such as sequences, trees, or grids. Unlike simple classification or regression, where each prediction is a single value or label, structured prediction models outputs that are made up of multiple related elements. This approach is…