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transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Grokking-Deep-Learning

this repository accompanies the book "Grokking Deep Learning"

UGATIT

Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)

mxnet-the-straight-dope

An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.

POT

POT : Python Optimal Transport

mt-dnn

Multi-Task Deep Neural Networks for Natural Language Understanding

awesome-embedding-models

A curated list of awesome embedding models tutorials, projects and communities.

deep-learning-notes

Experiments with Deep Learning

deq

[NeurIPS'19] Deep Equilibrium Models

ldsc

LD Score Regression (LDSC)

latent_ode

Code for "Latent ODEs for Irregularly-Sampled Time Series" paper

trellisnet

[ICLR'19] Trellis Networks for Sequence Modeling

optimaltransport.github.io

Web site of the Computational Optimal Transport book

svae

code for Structured Variational Autoencoders

prob-stats

Probability and Statistics: a simulation-based introduction. An open-access book.

SLiM

SLiM is a genetically explicit forward simulation software package for population genetics and evolutionary biology. It is highly flexible, with a built-in scripting language, and has a cross-platform graphical modeling environment called SLiMgui.

Deep-Kernel-GP

Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood

pop_gen_cnn

Neural-Kernel-Network

Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326

paired_cell_inpainting

Self-supervised learning for microscopy images

npde

Nonparametric Differential Equation Modeling

vi-hds

Variational inference for hierarchical dynamical systems

CisRegModels

Scripts for building computational models of gene regulation with tensorflow

nssm-gp

Non-stationary spectral mixture kernels implemented in GPflow

Variational_Gradient_Matching_for_Dynamical_Systems

Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"

nonstationary-spectral-kernels

Implementation for Non-stationary Spectral Kernels (NIPS 2017)

gprsm

Gaussian Process Regression using Spectral Mixture in GPflow

levy-spectral-kernel-learning

EVEE-Tools

EVEE-Tools is a suite of scripts for analyzing expression evolution across species.

LiMMBoAnalysis