girshick's repositories
tensorflow-mnist-tutorial
Sample code for "Tensorflow and deep learning, without a PhD" presentation and code lab.
ActiveBoundary
Active Decision Boundary Annotation with Deep Generative Models
convgp
Convolutional Gaussian processes based on GPflow.
MOE
A global, black box optimization engine for real world metric optimization.
nonconformist
Python implementation of the conformal prediction framework.
scala-cp
Conformal Prediction in Scala
rllab
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
BayesPy
Bayesian Inference Tools in Python
tensorflow-vgg
VGG19 and VGG16 on Tensorflow
spearmint
Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012
Mixture-Density-Networks-for-distribution-and-uncertainty-estimation
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
odin-pytorch
Principled Detection of Out-of-Distribution Examples in Neural Networks
dqn
Implementation of q-learning using TensorFlow
RandomForest
Julia implementation of random forests for classification and regression with conformal prediction
deep-rl
Collection of Deep Reinforcement Learning algorithms
grad-cam
[ICCV 2017] Torch code for Grad-CAM
elbow
Flexible Bayesian inference using TensorFlow
kernel-ep
kernel-based just-in-time learning for expectation propagation
Tensorflow_Deep_Taylor_LRP
Layerwise Relevance Propagation with Deep Taylor Series in TensorFlow
vbmds
Variational Bayesian Multi-dimensional Scaling Gaussian Process
bayesian_dense
Bayesian Weight Uncertainty Dense Layer for Keras
deep-ensemble-uncertainty
An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)
Active-Learning-Bayesian-Convolutional-Neural-Networks
Active Learning on Image Data using Bayesian ConvNets
phd-thesis
Repository of my thesis "Understanding Random Forests"
bayesian-nn-uncertainty
Classification uncertainty using Bayesian neural networks
uncertainty_gbm
Sklearn implementation of GBM to predict mu(X) and std(X) on heteroscedastic data
Dyna-H-Dyna-Q-Qlearning
Implementacion de los experimentos del paper Dyna-H A heuristic planning reinforcment learning algorithm applied to role playing game strategy decision systems
Probabilistic-Backpropagation
Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
deepGPy
Deep GPs with GPy