Stars
scikit-learn: machine learning in Python
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
The fundamental package for scientific computing with Python.
State-of-the-Art Text Embeddings
Statsmodels: statistical modeling and econometrics in Python
Cross-platform lib for process and system monitoring in Python
Deep universal probabilistic programming with Python and PyTorch
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
Fast, flexible and easy to use probabilistic modelling in Python.
A python package to analyze and compare voices with deep learning
Python library for causal inference and probabilistic modeling.
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
A Python library that helps data scientists to infer causation rather than observing correlation.
A comprehensive reference for all topics related to Natural Language Processing
A collection of scripts to set up MongoDB test environments and parse and visualize MongoDB log files.
A large-scale dataset of both raw MRI measurements and clinical MRI images.
Source code and dataset for ACL 2019 paper "ERNIE: Enhanced Language Representation with Informative Entities"
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multi…
Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch.
A universal time series representation learning framework
DAGs with NO TEARS: Continuous Optimization for Structure Learning
A Python implementation of active inference for Markov Decision Processes
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch
Causal Effect Inference with Deep Latent-Variable Models
Turn SymPy expressions into trainable JAX expressions.
A JAX-based research framework for differentiable and parallelizable acoustic simulations, on CPU, GPUs and TPUs