Companion

Cubie
Publications
Resources

SmallData Symposium 2024

Small Data Companion

We want to share our research with the world - no matter the level of expertise. To this end, we have developed the Small Data Companion. Below, you can browse our publications, via the publications tab or see all resources related to our publications in the resources tab. Each publication has been tagged with a coloured bar to show whether it relates to Similarity, Transfer, Uncertainty or a combination of these concepts.

Not sure where to start? Chat to our Cubie or find out more about out concepts in the Our Mission section above!

Cubie

Chat with our Chatbot Cubie, who knows all about Small Data research

Publications

Find all our publications here

Resources

Find datasets, tutorials, code, software and other resources related to our publications here

Below you will find a list of publications produced by our consortium. Each publication has been tagged by our researchers with categories such as clinical data or clustering, based on its content

You can combine categories using both AND and OR. For example: (Category A AND Category B)

You can further refine your search using the additional filters below. For example, you can filter for publications that include a dataset via the "All resources" tab, or filter by Small Data projects or people. The free text search can search across publication titles, authors, and abstracts.

OR AND
Artificial Neural Network: Autoencoder
Artificial Neural Network: Convolutional Neural Network
Artificial Neural Network: Long Short-Term Memory networks
Artificial Neural Network: Other
Artificial Neural Network: Recurrent Neural Network
Artificial Neural Network: Transformers
Automated Machine Learning
Bayes
Biological pathway and network
C++
Causal Inference
Clinical Data
Clustering
Computer Vision
Decision Tree
Dimensionality Reduction
Domain Adaptation
Embeddings
Ensemble
Few-shot Learning
Foundation model: Large Language Model
Foundation model: Other
Foundation model: TabPFN
Generative Model
Genetic Algorithms
Genomics
Graph Data
Hidden Markov Models
Hyperparameter Optimization
Imaging Data
In-Context Learning
Integration
Julia
k-nearest neighbors
Language Translator
Latent Space
Linear Models
Longitudinal Data
MATLAB
Maximum Likelihood
Metabolomics
Monte Carlo Simulation
Multi-omics
Multi-Task Learning
Multilabel Classification
Multi modal
Natural Language Processing
Noise Filtering
Non-linear technique
Optimization
Ordinary Differential Equations
Outlier Detection
Pharmacological and Drug
Prediction
Proteomics
Python
Quantifying uncertainty
R
Regression
Regularization
Reinforcement Learning
Self-supervised Learning
Semi-supervised Learning
Signal Processing
Similarity
Speech
Statistical testing
Stochastic Process
Stock Market Prediction
Supervised Learning
Support Vector Machine
Synthetic Data
Tabular Data
Text Processing
Time Series
Transcriptomics
Transfer Learning
Unsupervised Learning

Administrative Manager

Marc Schumacher

Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –
University of Freiburg