jthickstun/anticipation

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Python
License
Apache License 2.0
Created over 1 year ago
Updated 3 months ago

jthickstun/anticipation

jthickstun

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Anticipatory Autoregressive Models

watermark

Code for watermarking language models

pytorch_musicnet

PyTorch DataSet and Jupyter demos for MusicNet

Jupyter Notebook

basis-separation

Implementation of the BASIS algorithm for source separation with deep generative priors

thickstun2018invariances

Experiments for Invariances and Data Augmentation for Supervised Music Transcription

Jupyter Notebook

thickstun2017learning

Experiments for Learning Features of Music From Scratch, ICLR 2017

Jupyter Notebook

alignment-eval

Dataset and evaluation pipeline for music-to-score alignment

Jupyter Notebook

lean

Some experiments with the Lean proof assistant

mini-musicnet

The mini-MusicNet dataset

Jupyter Notebook

ismir2019coupled

Experiments for Coupled Recurrent Networks for Polyphonic Music Composition

Jupyter Notebook

gm-hw1

Homework 1 for Generative Models

Jupyter Notebook

gm-hw2

Homework 2 for Generative Models

Jupyter Notebook

gm-hw3

Homework 3 for Generative Models