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robustrnn

rotnet

sae

Semantic Autoencoder for Zero-shot Learning (Spotlight), CVPR 2017

scalablekmm

score-zeroshot

Semantically consistent regularizer for zero-shot learning

sebr

Robust Bayesian Neural Networks by Spectral Expectation Bound Regularization

self-ensemble-visual-domain-adapt

Code repository for the small image experiments our paper 'Self-ensembling for Domain Adaptation'

senteval

A python tool for evaluating the quality of sentence embeddings.

siamese-triplet

Siamese and triplet networks with online pair/triplet mining in PyTorch

spotlight

Deep recommender models using PyTorch.

stable-baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

sysid_l2fly

System Identification, Modeling, and Control of Linear and Nonlinear Systems

system-identification-ann

Couple of techniques that use Artificial Neural Networks to identify dynamical (especially nonlinear) systems

taskcv-2017-public

tencent-ml-images

Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet

tensorflow-generative-model-collections

Collection of generative models in Tensorflow

tensorflow-vgg

A VGG-19 implementation using Tensorflow

tensorflow_cookbook

Code for Tensorflow Machine Learning Cookbook

tensorflow_multigpu_imagenet

Tensorflow code for training different architectures(DenseNet, ResNet, AlexNet, GoogLeNet, VGG, NiN) on ImageNet dataset + Multi-GPU support + Transfer Learning support

theano_exercises

Exercises for my tutorials on Theano

training-robust-neural-networks-using-lipschitz-bounds

Here you can find the code for the paper "Training robust neural networks using Lipschitz bounds"

transfer-learning

tags: transfer learning, domain adaptation, finetuning, one-shot learning, zero-shot learning.

transfer_learning_tutorial

A guide to transfer learning with inception-resnet-v2.

transferlearning

Everything about Transfer Learning and Domain Adaptation--迁移学习

variant_impedance_tracking_rl

variational_dropout

pytorch implementation of variational dropout

vcml

PyTorch implementation of paper "Visual Concept-Metaconcept Learner", NeruIPS 2019

vqa_lstm_cnn

Train a deeper LSTM and normalized CNN Visual Question Answering model. This current code can get 58.16 on OpenEnded and 63.09 on Multiple-Choice on test-standard.

vqs

VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation

walk-these-ways

Sim-to-real RL training and deployment tools for the Unitree Go1 robot.