Stars
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024
A Unified Framework for Quantifying Privacy Risk in Synthetic Data according to the GDPR
A curated list of awesome synthetic data tools (open source and commercial).
🛁 Clean Code concepts adapted for Python
Training PyTorch models with differential privacy
Productive, portable, and performant GPU programming in Python.
This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a community of users and contributors by focusing initially o…
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
Notebooks and various random fun
Plugin for nose or pytest that automatically reruns flaky tests.
This dataset code generates mathematical question and answer pairs, from a range of question types at roughly school-level difficulty.
A py.test plugin to validate Jupyter notebooks
A primer on software development best practices for computational chemistry
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
An Open Source Machine Learning Framework for Everyone
A primer on statistical mechanics for biochemists
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
🙈 Volkswagen detects when your tests are being run in a CI server, and makes them pass.
A document for the Living Journal of Computational Molecular Science (LiveCoMS) which describes basic training for molecular simulations (oriented towards molecular dynamics (MD)), providing some t…
An open source Python framework for transition interface and path sampling calculations.
How to analyze molecular dynamics data with PyEMMA