Atılım Güneş Baydin's repositories
tensorflow-forward-ad
Forward-mode Automatic Differentiation for TensorFlow
pyprob
PyTorch-based library for probabilistic programming and inference compilation
HyperGradientDescent
TensorFlow implementation of Hypergradient Descent modification of Adam algorithm
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
pytorch_nersc_wheel
PyTorch wheel installation file with performance optimization on CPU
anglican-infcomp
Clojure library for Inference Compilation
anglican-infcomp-examples
Examples for anglican-infcomp
autograd
Efficiently computes derivatives of numpy code.
entrofy
Participant selection for workshops and conferences made easy
zeppelin
Awesome conference website in 5 minutes.
CSCS-summer-school-2017
CSCS-ICS-DADSi Summer School: Accelerating Data Science with HPC, September 4 – 6, 2017
Sigma.DiffSharp
SigmaDiff is a custom version of DiffSharp for automatic functional differentiation with ndarrays.
probprog-for-lions
This repo contains example code, data and experiments related to the UAI 2017 submission: ''Interpreting Lion Behaviour with Nonparametric Probabilistic Programs'''
FreezeOut
Accelerate Neural Net Training by Progressively Freezing Layers
anglican
Probabilistic Programming System Anglican
nvidia-docker
Build and run Docker containers leveraging NVIDIA GPUs
PyTransit
Fast and easy transit light curve modeling using Python and Fortran.
pylightcurve
exoplanet lightcurve model
recnn
Repository for the code of "QCD-Aware Recursive Neural Networks for Jet Physics"
nips2016
A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2016
siplasplas
A library for C++ reflection and introspection
d-CGP
Implementation of the differential CGP (Cartesian Genetic Programming)
audi
Automated Differentiation for high degrees and multiple variables. Open source implementation of Differential Algebra
DeepNet
Deep.Net machine learning framework for F#
anglican-user
Anglican User Template
torch-autograd
Autograd automatically differentiates native Torch code
autodiff
Experiments with autodiff of various forms