We release a Python library for gradient-based hyperparameter optimization, implementing cutting-edge algorithms that leverage automatic differentiation to efficiently tune hyperparameters.

We release a cutting-edge Python library designed to streamline the optimization of discrete probability distributions in neural networks, offering a suite of advanced relaxation techniques compatible with PyTorch.

Various approaches to modeling the spread of epidemics, differential equations and Markov processes.

Comparison of different methods of solving high-dimensional linear regression problems.

Application for generating presentations based on text files using topic modeling.