GitHub

c-lasso: a Python package for constrained sparse regression and classification

c-lasso is a Python package that enables sparse and robust linear regression and classification with linear equality constraints on the model parameters. For detailed info, one can check the ...
Nature

Continuous-variable quantum passive optical network

To establish a scalable and secure quantum network, a critical milestone is advancing from basic point-to-point quantum key distribution (QKD) systems to the development of inherently multi-user ...
Frontiers

Learning from the past: reservoir computing using delayed variables

Reservoir computing is a machine learning method that is closely linked to dynamical systems theory. This connection is highlighted in a brief introduction to the general concept of reservoir ...
PNAS

Joint trajectory inference for single-cell genomics using deep learning with a mixture prior

We propose an approach for joint trajectory analysis of multiple single-cell sequencing data, combining Bayesian hierarchical models with variational autoencoders. Based on a coherent statistical ...
Nature

Learnable latent embeddings for joint behavioural and neural analysis

CEBRA can leverage continuous behavioural (kinematics, actions) as well as other discrete variables (trial ID, rewards, brain-area ID and so on). Additionally, user-defined information about desired ...
Frontiers

Data Science for Weather Impacts on Crop Yield

Private businesses in sectors, such as food, energy, and retail, as well as public sector and federal agencies are interested in the predictive understanding of weather impacts on crop yield, which is ...