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amortizedcausaldiscovery

Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

braindecode_from_hubertjb

Deep learning software to decode EEG or MEG signals

causal-inference-via-nonlinear-forecasting

deep-scientific-discovery

An implementation of the paper 'Using Deep Networks for Scientific Discovery in Physiological Signals'

graph-u-nets

Pytorch implementation of Graph U-Nets (ICML19)

ivae

VAEs and nonlinear ICA: a unifying framework

ivae-1

VAEs and nonlinear ICA: a unifying framework

mfcvae

[NeurIPS 2021] 🏁 Multi-Facet Clustering Variatonal Autoencoders (MFCVAE) 🏁 A class of variational autoencoders to find multiple disentangled clusterings of data. Official PyTorch implementation.

minimal

Minimal is a Jekyll theme for GitHub Pages

mmpf

Implementation of Minimax Pareto Fairness framework

nlp_unsupervised_graphical_representations

probml_final_project

A repository for our group's final project in Duke University's STA 561 Probabilistic ML course.

pytorch-vade

My implementation of Variational Deep Embedding (VaDE) using Pytorch

scikit_tt

Tensor Train Toolbox

skccm

Convergent Cross Mapping in Scikit Learn's style

ssl_baselines_for_biosignal_feature_extraction

Implementations of various published works on self-supervised learning approaches to biosignal feature extraction.

tdnet

Learning a Single Tucker Decomposition Network for Lossy Image Compression with Multiple Bits-Per-Pixel Rates (TIP 2020)

tensortools

A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA

thinkerinvariance

time_delay_dmd

Dynamic Mode Decomposition (DMD) in Principal Component Trajectory Coordinates

towards-neural-programming-interfaces

The code repository associated with the NeurIPS 2020 paper: "Towards Neural Programming Interfaces"

zacharycbrown.github.io