Pinned Repositories
aqml
Amons-based quantum machine learning for quantum chemistry
AutomaticLossWeightingPyTorch
PyTorch implementation of https://arxiv.org/abs/1705.07115 loss weighting
bayesian-neural-network-blogpost
Building a Bayesian deep learning classifier
BNMTF_ARD
Python code for "Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation", published at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017).
chembl_webresource_client
Official Python client for accessing ChEMBL API.
deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
dl-uncertainty
"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).
EMOGI
An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.
graphdg
Generative model for molecular distance geometry
GroundHog
Library for implementing RNNs with Theano
unsterbliche's Repositories
unsterbliche/TranSiGen
unsterbliche/EMOGI
An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.
unsterbliche/MultipleComparisons
unsterbliche/SyntaLinker
Automatic Fragment Linking with Deep Conditional Transformer Neural Networks
unsterbliche/nonconformist
Python implementation of the conformal prediction framework.
unsterbliche/PyTorch-BayesianCNN
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
unsterbliche/psikit
psi4+RDKit
unsterbliche/graphdg
Generative model for molecular distance geometry
unsterbliche/aqml
Amons-based quantum machine learning for quantum chemistry
unsterbliche/dl-uncertainty
"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).
unsterbliche/AutomaticLossWeightingPyTorch
PyTorch implementation of https://arxiv.org/abs/1705.07115 loss weighting
unsterbliche/UQ_BNN
Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
unsterbliche/BNMTF_ARD
Python code for "Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation", published at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017).
unsterbliche/paccmann
PaccMann training models
unsterbliche/multi-task-image-classification
Multi-task learning for image classification implemented in PyTorch.
unsterbliche/Knet.jl
Koç University deep learning framework.
unsterbliche/chembl_webresource_client
Official Python client for accessing ChEMBL API.
unsterbliche/deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
unsterbliche/test
test
unsterbliche/bayesian-neural-network-blogpost
Building a Bayesian deep learning classifier
unsterbliche/GroundHog
Library for implementing RNNs with Theano