Mosh is a remote terminal application that allows client roaming, supports intermittent connectivity, and provides intelligent local echo and line editing of user keystrokes. It's a replacement for SSH that's more robust and responsive, especially over Wi-Fi, cellular, and long-distance links.

autossh is a program to start a copy of ssh and monitor it, restarting it as necessary should it die or stop passing traffic.

Endlessh is an SSH tarpit that very slowly sends an endless, random SSH banner. It keeps SSH clients locked up for hours or even days at a time. The purpose is to put your real SSH server on another port and then let the script kiddies get stuck in this tarpit instead of bothering a real server.

Since the tarpit is in the banner before any cryptographic exchange occurs, this program doesn't depend on any cryptographic libraries. It's a simple, single-threaded, standalone C program. It uses poll() to trap multiple clients at a time.

Liboop is a low-level event loop management library for POSIX-based operating systems. It supports the development of modular, multiplexed applications which may respond to events from several sources. It replaces the "select() loop" and allows the registration of event handlers for file and network I/O, timers and signals. Since processes use these mechanisms for almost all external communication, liboop can be used as the basis for almost any application.

The SSH2 protocol implemented in OpenSSH is standardised by the IETF secsh working group and is specified in several RFCs and drafts. It is composed of three layered components:

The transport layer provides algorithm negotiation and a key exchange. The key exchange includes server authentication and results in a cryptographically secured connection: it provides integrity, confidentiality and optional compression.

The user authentication layer uses the established connection and relies on the services provided by the transport layer. It provides several mechanisms for user authentication. These include traditional password authentication as well as public-key or host-based authentication mechanisms.

The connection layer multiplexes many different concurrent channels over the authenticated connection and allows tunneling of login sessions and TCP-forwarding. It provides a flow control service for these channels. Additionally, various channel-specific options can be negotiated.

The SSH2 protocol implemented in OpenSSH is standardised by the IETF secsh working group and is specified in several RFCs and drafts. It is composed of three layered components:

The transport layer provides algorithm negotiation and a key exchange. The key exchange includes server authentication and results in a cryptographically secured connection: it provides integrity, confidentiality and optional compression.

The user authentication layer uses the established connection and relies on the services provided by the transport layer. It provides several mechanisms for user authentication. These include traditional password authentication as well as public-key or host-based authentication mechanisms.

The connection layer multiplexes many different concurrent channels over the authenticated connection and allows tunneling of login sessions and TCP-forwarding. It provides a flow control service for these channels. Additionally, various channel-specific options can be negotiated.

adcli is a command‐line tool to join a computer to an Active Directory domain. It can also update the machine password and manage user, group and computer accounts for a domain.

SSSD is a system daemon. Its primary function is to provide access to identity and authentication remote resource through a common framework that can provide caching and offline support to the system. It provides PAM and NSS modules, and in the future will support D-BUS based interfaces for extended user information. It also provides a better database to store local users as well as extended user data.

DING-LIBS (DING Is Not Glib) are a set of small, useful libraries that the System Security Services Daemon (SSSD) uses and makes available to other projects. They include: libdhash, an implementation of a dynamic hash table which will dynamically resize to achieve optimal storage and access time properties; ini_config, a library for parsing and managing INI files; path_utils, a library to manage UNIX paths and subsets of paths; collection, a generic, hierarchical grouping mechanism for complex data sets; ref_array, a dynamically-growing, reference-counted array; libbasicobjects, a set of fundamental object types for C.

Rapid, simulation-based exact (restricted) likelihood ratio tests for testing the presence of variance components/nonparametric terms for models fit with nlme::lme(), lme4::lmer(), lmeTest::lmer(), gamm4::gamm4(), mgcv::gamm() and SemiPar::spm().

This package provides a library for Probabilistic Graphical Models. It can be used for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

GetDist is a Python package for analysing Monte Carlo samples, including correlated samples from Markov Chain Monte Carlo (MCMC).

This package helps accessing files relative to a project root. It provides helpers for robust, reliable and flexible paths to files below a project root. The root of a project is defined as a directory that matches a certain criterion, e.g., it contains a certain regular file.

This package provides an R wrapper around the fast T-distributed Stochastic Neighbor Embedding using a Barnes-Hut implementation.

This package provides simple utility functions that are shared across several packages maintained by the Tanay lab.

Enumerable::Statistics provides some methods to calculate statistical summary in arrays and enumerables.

This package embeds the SQLite database engine in R and provides an interface compliant with the DBI package. The source for the SQLite engine (version 3.8.8.2) is included.

This is a package for Non-Negative Linear Models (NNLM). It implements fast sequential coordinate descent algorithms for non-negative linear regression and non-negative matrix factorization (NMF). It supports mean square error and Kullback-Leibler divergence loss. Many other features are also implemented, including missing value imputation, domain knowledge integration, designable W and H matrices and multiple forms of regularizations.

MAPIE allows you to easily estimate prediction intervals (or prediction sets) using your favourite scikit-learn-compatible model for single-output regression or multi-class classification settings.

Prediction intervals output by MAPIE encompass both aleatoric and epistemic uncertainties and are backed by strong theoretical guarantees thanks to conformal prediction methods intervals.

Given a regression model, segmented updates the model by adding one or more segmented (i.e., piecewise-linear) relationships. Several variables with multiple breakpoints are allowed.

emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC).

This package provides an implementation of robust location and scatter estimation and robust multivariate analysis with high breakdown point.

This package provides functionalities to build and manipulate probability distributions of the skew-normal family and some related ones, notably the skew-t family, and provides related statistical methods for data fitting and diagnostics, in the univariate and the multivariate case.

Various definitions for a high-dimensional median exist and this Python package provides a number of fast implementations of these definitions. Medians are extremely useful due to their high breakdown point (up to 50% contamination) and have a number of nice applications in machine learning, computer vision, and high-dimensional statistics.