In recent times, image segmentation has been involving everywhere including disease
diagnosis to autonomous vehicle driving. In computer vision, this image segmentation is one …

Procedural content generation in video games has a long history. Existing procedural
content generation methods, such as search-based, solver-based, rule-based and grammar …

Large Language Models (LLMs) are powerful tools, capable of leveraging their training on
natural language to write stories, generate code, and answer questions. But can they …

Physics-informed neural networks (PINNs) have enabled significant improvements in
modelling physical processes described by partial differential equations (PDEs) and are in …

Synthetic time series are often used in practical applications to augment the historical time
series dataset, amplify the occurrence of rare events and also create counterfactual …

Procedural content generation (PCG) refers to the practice of generating game content, such
as levels, quests or characters, algorithmically. Motivated by the need to make games …

In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and
capability in image generation and dimensionality reduction. The combination of VAE and …

Crafting a rich and unique environment is crucial for fictional world-building, but can be
difficult to achieve since illustrating a world from scratch requires time and significant skill …

Recent progress in reinforcement learning (RL) has started producing generally capable
agents that can solve a distribution of complex environments. These agents are typically …

When studying robots collaborating with humans, much of the focus has been on robot
policies that coordinate fluently with human teammates in collaborative tasks. However, less …