Pytorch-PCGradPytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
Stars: ✭ 179 (+426.47%)
Mutual labels: mnist, multi-task-learning
Fashion MnistA MNIST-like fashion product database. Benchmark 👇
Stars: ✭ 9,675 (+28355.88%)
Mutual labels: mnist, fashion-mnist
gans-2.0Generative Adversarial Networks in TensorFlow 2.0
Stars: ✭ 76 (+123.53%)
Mutual labels: mnist, fashion-mnist
cups-rlCustomisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"
Stars: ✭ 38 (+11.76%)
Mutual labels: transfer-learning, multi-task-learning
playing with vaeComparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST
Stars: ✭ 53 (+55.88%)
Mutual labels: mnist, fashion-mnist
Mask-YOLOInspired from Mask R-CNN to build a multi-task learning, two-branch architecture: one branch based on YOLOv2 for object detection, the other branch for instance segmentation. Simply tested on Rice and Shapes. MobileNet supported.
Stars: ✭ 100 (+194.12%)
Mutual labels: multi-task-learning
MinTLMinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems
Stars: ✭ 61 (+79.41%)
Mutual labels: transfer-learning
FaceClassification TensorflowBuilding a Neural Network that classifies faces using OpenCV and Tensorflow
Stars: ✭ 37 (+8.82%)
Mutual labels: transfer-learning
awesome-list-of-awesomesA curated list of all the Awesome --Topic Name-- lists I've found till date relevant to Data lifecycle, ML and DL.
Stars: ✭ 259 (+661.76%)
Mutual labels: transfer-learning
DeepSegmentorA Pytorch implementation of DeepCrack and RoadNet projects.
Stars: ✭ 152 (+347.06%)
Mutual labels: multi-task-learning
LSTM-GRU-from-scratchLSTM, GRU cell implementation from scratch in tensorflow
Stars: ✭ 30 (-11.76%)
Mutual labels: fashion-mnist
AdaBound-tensorflowAn optimizer that trains as fast as Adam and as good as SGD in Tensorflow
Stars: ✭ 44 (+29.41%)
Mutual labels: mnist
cmdCentral Moment Discrepancy for Domain-Invariant Representation Learning (ICLR 2017, keras)
Stars: ✭ 53 (+55.88%)
Mutual labels: transfer-learning
tensorflow-mnist-convnetsNeural nets for MNIST classification, simple single layer NN, 5 layer FC NN and convolutional neural networks with different architectures
Stars: ✭ 22 (-35.29%)
Mutual labels: mnist
mnist-challengeMy solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
Stars: ✭ 68 (+100%)
Mutual labels: mnist
Transfer-LearningInception V3 for Transfer Learning on Cats and Dogs
Stars: ✭ 17 (-50%)
Mutual labels: transfer-learning
chainer-ADDAAdversarial Discriminative Domain Adaptation in Chainer
Stars: ✭ 24 (-29.41%)
Mutual labels: mnist