Rob Romijnders

AE_ts. Auto encoder for time series

LSTM_tsc. An LSTM for time-series classification

weight_uncertainty. Implementing Bayes by Backprop

CNN_tsc. A CNN for time-series classification

RNN_basketball. LSTM + MDN for basketball trajectories

bigclam. Implements the bigCLAM algorithm

ssl_graph. Semi supervised learning on graphs

bayes_nn. Uncertainty interpretations of the neural network

cnn_music. A CNN for music genre classification and TSC in general

bandit. Implementation of Counterfactual risk minimization

segm. Simple Semantic Segmentation

EM. visualizing Expectation Maximization

VAE_rec. Variational Recurrent Auto Encoder

vi_normal. Variational Inference for a Normal Distribution

EDS. Github Repo for Eindhoven Data Science MeetUp

dan. Domain Agnostic Normalization layer for Unsupervised Domain Adaptation

tensorflow_basic. Basic start of TensorFlow with TensorBoard

attention. An elementary example of soft attention

hypothesis_kalman. Hypothesis testing for time series: two buckets are from same source or different?

LSTM_cpd. LSTM for change point detection

ladder. LADDER network after Harri Valpola

ts_clust. WIP to cluster time series

dpm. Dirichlet Process Mixtures

overview. Overview diagram and lists of Machine Learning

awesome_distributions. Scribbles about marginalization property of Gaussian and aggregation property of Dirichlet

ssl. Implementation of self ensembling for semi supervised learning

cs231n. Files for the cs231n course at Stanford

indian_buffet. Indian buffet latent variable model

FCN. Fully Convolutional Network

rbm. Restricted Boltzmann Machine

q_learning. Implementation of epsilon-greedy q-learning for robot on 2D grid

RAM. Recurrent Attention Model

occam. Implementing Occam's razor from the Statistical and Bayesian views.

VAE. Variational Auto encoder

DRAW. DRAW

rbfn_learnable. RBFN with learnable RBF parameters

hypothesis_testing. Project on hypothesis testing

ssl_rep. Combining insights from representation learning and semi supervised learning

mcmc_proposals. Compare different proposal distro's for MCMC

bbvi. Comparing variance of gradient estimators for BBVI

pydata24. Jupyter Notebook

bayesian_model_comparison. Three approaches for Bayesian model comparison

hacking_180824. hacking_180824

far_away. Exploring linear classifiers on inputs far away from the training data

dpbmm. Dirichlet Process Mixture model for Multinoulli distributions

talks. repo for my talks

trees_ensemble. This projects aggregates a Bagging, Random Forest and MLP classifier for data competition

RBFN_two_MNIST. Radial basis function network for two classes of the MNIST dataset