Blogs
Our blogs are constructed in three parts: (1) high-level blogs that aim to motivate people with either AI or Science background to learn and join this exciting interdisciplinary field, (2) hands-on blogs on each individual topic (either an AI technique or a scientific problem/discipline), (3) knowledge base that collects the basic explanations of terminologies.
Announcing AI for Science Blogs
- What we are doing? Why we are doing? Who are we? How do you get involved?
- Why is AI for Science an exciting field for people with Science backgrounds?
Scientific Discovery in the era of AI
- Why is AI for Science an exciting field for people with AI backgrounds?
- Molecular simulation is a computational method used to model and study the behavior of molecules and chemical systems.
- Gaussian processes are a central model in probabilistic machine learning with particularly favourable properties for uncertainty quantification and Bayesian optimisation.
- Causal machine learning aims to identify the causal relationships that govern various observed phenomena is an essential objective across diverse scientific disciplines, as it helps researchers understand the underlying mechanisms and facilitate principled analysis.
- Statistical learning theory provides theoretical tools to analyze deep learning models.
- Optimization is essential for deep learning to train and update/search model parameters.
- Graph Machine Learning enables machine learning to explicitly model graph-structured data.
- Reinforcement Learning concerns about how an intelligent agent takes actions with feedback from an environment.
- Quantum Science is a branch of physics that describes the behavior of matter and energy on a very small scale, such as atoms and subatomic particles.
- Computational Sustainability is an emerging field which uses computational ideas and methods to address the United Nations Sustainable Development Goals (UN SDGs).
- Structural biology deals with structural analysis of living material (formed, composed of, and/or maintained and refined by living cells) at every level of organization.
- Quantum Chemistry focuses on the application of quantum mechanics to chemical systems, particularly towards the quantum-mechanical calculation of electronic contributions to physical and chemical properties of molecules, materials, and solutions at the atomic level.
- Equivariant neural networks are designed to encode symmetries into neural architectures.
- Basic terminologies (Physics, Chemistry, Biology, Pharma) and short explanations.