CaRAML is a community of machine learning and artificial intelligence researchers at the University of Cambridge.
Gaussian Processes, Probabilistic Machine Learning, Dimensionality Reduction, Single-Cell Data Analysis
Neural Differential Equations, Generative Models, Diffusion Models, Feature Selection, Transfer Learning
Data-efficient machine learning, Feature Selection, High-dimensional data
Artificial Intelligence, Structural Biology, Drug Discovery, Generative models, Self-supervised Learning
Multimodal representations, Multiscale biological models, Computational Pathology, Spatial Transcriptomics, Deep Learning
Graph representation learning, ML framework design, Computational biology
Bioinformatics, Precision medicine, Social good, Unsupervised learning, Deep learning
Artificial Intelligence, Biotechnology, Protein Design, Environmental Applications, Quantum Physics
Machine Learning, ML applications in medicine, biology and neuroscience
Computational Biology, Bioinformatics, Machine Learning, Artificial Intelligence, Complex Networks
Artificial Intelligence, Machine Learning
Graph representation learning, Meta-learning, Multimodal learning, Real-world challenges
Automated Machine Learning, ML systems, ML security
Computational Biology, Bayes, Multi-modal learning, Biophysics, Active Learning, MARL
Deep Learning, Computer Vision
Geometric Deep Learning, Graph Representation Learning, Graph Neural Networks, Algorithmic Reasoning, Computational Biology
Explainable Graph Neural Networks, Complex System, Temporal Networks, Temporal Graph Mining
High Performance Computing, Parallel Computing, Distributed Computing, Deep Learning, Machine Learning