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David Hockaday's Projects

diffy icon diffy

Code for pre-print "Measuring dissimilarity with diffeomorphism invariance" (2022)

difw icon difw

Expressive diffeomorphic transformations based on the closed-form integration of continuous piecewise affine velocity functions.

dilate icon dilate

Code for our NeurIPS 2019 paper "Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models"

disentanglement_lib icon disentanglement_lib

disentanglement_lib is an open-source library for research on learning disentangled representations.

dit icon dit

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

djmix-analysis icon djmix-analysis

Code for "A Computational Analysis of Real-World DJ Mixes using Mix-To-Track Subsequence Alignment" ISMIR 2020

djtools icon djtools

Libraries for reading, writing and converting media library information between different DJ Software applications.

djtransgan icon djtransgan

"Automatic DJ Transitions with Differentiable Audio Effects and Generative Adversarial Networks", ICASSP 2022

djtransgan-dg-pipeline icon djtransgan-dg-pipeline

"Automatic DJ Transitions with Differentiable Audio Effects and Generative Adversarial Networks", ICASSP 2022 (Data Generation Pipeline)

dl-4-tsc icon dl-4-tsc

Deep Learning for Time Series Classification

dldnn icon dldnn

Neural Network optimizer for DLD design

dlr icon dlr

The accompanying code for "Simplifying and Understanding State Space Models with Diagonal Linear RNNs" (Ankit Gupta, Harsh Mehta, Jonathan Berant).

dmelodies_controllability icon dmelodies_controllability

Code for running experiments in our ISMIR'21 paper titled: "Is Disentanglement enough? On Latent Representations for Controllable Music Generation"

dmelodies_dataset icon dmelodies_dataset

Dataset to study disentanglement in the context of symbolic music. Published as an ISMIR'20 paper titled: "dMelodies: A Music Dataset for Disentanglement Learning"

dm_control icon dm_control

DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

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