Nicki Skafte Detlefsen (SkafteNicki)

SkafteNicki

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Location:Denmark

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Nicki Skafte Detlefsen's repositories

dtu_mlops

Exercises and supplementary material for the machine learning operations course at DTU.

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libcpab

CPAB Transformations: finite-dimensional spaces of simple, fast, and highly-expressive diffeomorphisms derived from parametric, continuously-defined, velocity fields in Numpy, Tensorflow and Pytorch

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cuda_expm

Matrix exponential in cuda for pytorch and tensorflow

unsuper

Some unsupervised algorithms

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py_uci

Python library for loading data from the UCI Machine Learning Repository

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pytorch-metrics

Metrics for pytorch

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pytorch-lightning

The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate

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cookiecutter-data-science

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

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cusolver_example

Example of calling cusolver from python by using pytorch

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deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

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Deep_LMNN

LMNN algorithm in tensorflow

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delira

Lightweight framework for fast prototyping and training deep neural networks with PyTorch and TensorFlow

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ignite

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

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just-the-docs

A modern, high customizable, responsive Jekyll theme for documention with built-in search.

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minima-sidebar

Jekyll Minima theme with TOC in sidebar

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minimal-mistakes

:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

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pyclust

My own personal scripts for easy working with the cluster at my work

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pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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scikit-learn

scikit-learn: machine learning in Python

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SkafteNicki.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

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tape

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

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tape-1

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

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vae_variance_funcs

Trying to fix the arbitrariness of the variance function in VAEs

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vision

Datasets, Transforms and Models specific to Computer Vision

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