Alternatives and similar repositories for BCFWstruct

Users that are interested in BCFWstruct are comparing it to the libraries listed below

• locuslab / newton_admm
  A Newton ADMM based solver for Cone programming.
  ☆39Updated 7 years ago
• imurray / chol-rev
  Backpropagate derivatives through the Cholesky decomposition
  ☆58Updated 5 years ago
• Simon-Lacoste-Julien / linearFW
  Frank-Wolfe optimization variants with a linear convergence rate
  ☆22Updated 9 years ago
• mahito-sugiyama / Legendre-decomposition
  Legendre decomposition for tensors
  ☆13Updated 6 years ago
• cvxgrp / cvxflow
  ☆67Updated 7 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 9 years ago
• davmre / gprf
  Gaussian Process Random Fields
  ☆21Updated 9 years ago
• bshahr / torch-dngo
  Torch implementation of the Deep Network for Global Optimization (DNGO)
  ☆51Updated 8 years ago
• andre-martins / AD3
  Alternating Directions Dual Decomposition
  ☆69Updated 5 years ago
• nitromannitol / stochastic-quasi-newton
  modular implementation of new algorithm
  ☆13Updated 11 years ago
• zhegan27 / dsbn_aistats2015
  The Matlab Code for the AISTATS 2015 paper "Learning Deep Sigmoid Belief Network with Data Augmentation"
  ☆13Updated 9 years ago
• philipphennig / probabilistic-numerics.org
  This repository houses the code for the community website http://www.probabilistic-numerics.org
  ☆35Updated 5 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• uoguelph-mlrg / Theano-MPI
  MPI Parallel framework for training deep learning models built in Theano
  ☆54Updated 7 years ago
• yaoli / nade_k
  An iterative neural autoregressive distribution estimator (NADE-K)
  ☆26Updated 10 years ago
• svaiter / pyprox
  Proximal algorithms made easy in Python
  ☆59Updated 8 years ago
• karlstratos / cca
  ☆10Updated 10 years ago
• stan-dev / nomad
  Fast autodiff.
  ☆19Updated 10 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 7 years ago
• kd383 / GPML_SLD
  Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)
  ☆18Updated 7 years ago
• ucla-vision / parle
  ☆38Updated 7 years ago
• mdenil / acdc-torch
  ACDC: A Structured Efficient Linear Layer
  ☆43Updated 9 years ago
• hoytak / pyksvd
  A highly optimized, parallel implementation of the Batch-OMP version of the KSVD learning algorithm.
  ☆78Updated 5 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 10 years ago
• kuleshov / tensor-factorization
  Tensor Factorization via Matrix Factorization
  ☆34Updated 9 years ago
• cchangyou / Santa
  Code for the Santa algorithm for deep learning
  ☆17Updated 7 years ago
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 8 years ago
• epfl-lts2 / pyunlocbox
  A Python convex optimization package using proximal splitting methods
  ☆111Updated last year
• jaanli / proximity_vi
  This code accompanies the proximity variational inference paper.
  ☆18Updated 6 years ago
• frank-hutter / fanova
  Functional ANOVA
  ☆27Updated 10 years ago