Alae[CVPR2020] Adversarial Latent Autoencoders
Stars: ✭ 3,178 (+13717.39%)
generative deep learningGenerative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)
Stars: ✭ 24 (+4.35%)
Pytorch Pix2pixPytorch implementation of pix2pix for various datasets.
Stars: ✭ 74 (+221.74%)
Delving Deep Into GansGenerative Adversarial Networks (GANs) resources sorted by citations
Stars: ✭ 834 (+3526.09%)
PsganPeriodic Spatial Generative Adversarial Networks
Stars: ✭ 108 (+369.57%)
GiqaPytorch implementation of Generated Image Quality Assessment
Stars: ✭ 100 (+334.78%)
deep-blueberryIf you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!
Stars: ✭ 17 (-26.09%)
SeganSpeech Enhancement Generative Adversarial Network in TensorFlow
Stars: ✭ 661 (+2773.91%)
Pytorch Seq2seqTutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Stars: ✭ 3,418 (+14760.87%)
Text-Classification-LSTMs-PyTorchThe aim of this repository is to show a baseline model for text classification by implementing a LSTM-based model coded in PyTorch. In order to provide a better understanding of the model, it will be used a Tweets dataset provided by Kaggle.
Stars: ✭ 45 (+95.65%)
TorchganResearch Framework for easy and efficient training of GANs based on Pytorch
Stars: ✭ 1,156 (+4926.09%)
GDPPGenerator loss to reduce mode-collapse and to improve the generated samples quality.
Stars: ✭ 32 (+39.13%)
gcWGANGuided Conditional Wasserstein GAN for De Novo Protein Design
Stars: ✭ 38 (+65.22%)
caltech birdsA set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.
Stars: ✭ 29 (+26.09%)
abae-pytorchPyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'
Stars: ✭ 52 (+126.09%)
MavaA library of multi-agent reinforcement learning components and systems
Stars: ✭ 355 (+1443.48%)
MelNet-SpeechGenerationImplementation of MelNet in PyTorch to generate high-fidelity audio samples
Stars: ✭ 19 (-17.39%)
fast-style-transfer-tutorial-pytorchSimple Tutorials & Code Implementation of fast-style-transfer(Perceptual Losses for Real-Time Style Transfer and Super-Resolution, 2016 ECCV) using PyTorch.
Stars: ✭ 18 (-21.74%)
BtcDetBehind the Curtain: Learning Occluded Shapes for 3D Object Detection
Stars: ✭ 104 (+352.17%)
photometric optimizationPhotometric optimization code for creating the FLAME texture space and other applications
Stars: ✭ 271 (+1078.26%)
Relation-Network-PyTorchImplementation of Relation Network and Recurrent Relational Network using PyTorch v1.3. Original papers: (RN) https://arxiv.org/abs/1706.01427 (RRN): https://arxiv.org/abs/1711.08028
Stars: ✭ 17 (-26.09%)
Ensemble-PytorchA unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
Stars: ✭ 407 (+1669.57%)
torch-metricsMetrics for model evaluation in pytorch
Stars: ✭ 99 (+330.43%)
srVAEVAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.
Stars: ✭ 56 (+143.48%)
attention-sampling-pytorchThis is a PyTorch implementation of the paper: "Processing Megapixel Images with Deep Attention-Sampling Models".
Stars: ✭ 25 (+8.7%)
fusion ganCodes for the paper 'Learning to Fuse Music Genres with Generative Adversarial Dual Learning' ICDM 17
Stars: ✭ 18 (-21.74%)
neural-question-generationPytorch implementation of Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks
Stars: ✭ 126 (+447.83%)
lowshot-shapebiasLearning low-shot object classification with explicit shape bias learned from point clouds
Stars: ✭ 37 (+60.87%)
DiffuseVAEA combination of VAE's and Diffusion Models for efficient, controllable and high-fidelity generation from low-dimensional latents
Stars: ✭ 81 (+252.17%)
genstarGeneration of Synthetic Populations Library
Stars: ✭ 17 (-26.09%)
Walk-TransformerFrom Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)
Stars: ✭ 26 (+13.04%)
graph-nvpGraphNVP: An Invertible Flow Model for Generating Molecular Graphs
Stars: ✭ 69 (+200%)
SelfOrganizingMap-SOMPytorch implementation of Self-Organizing Map(SOM). Use MNIST dataset as a demo.
Stars: ✭ 33 (+43.48%)
ddpm-proteinsA denoising diffusion probabilistic model (DDPM) tailored for conditional generation of protein distograms
Stars: ✭ 55 (+139.13%)
pytorch-serving[UNMAINTAINED] A starter pack for creating a lightweight responsive web app for Fast.AI PyTorch models.
Stars: ✭ 16 (-30.43%)
transganformerImplementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper
Stars: ✭ 137 (+495.65%)
vae-torchVariational autoencoder for anomaly detection (in PyTorch).
Stars: ✭ 38 (+65.22%)
nlp classificationImplementing nlp papers relevant to classification with PyTorch, gluonnlp
Stars: ✭ 224 (+873.91%)
FedLab-benchmarksStandard federated learning implementations in FedLab and FL benchmarks.
Stars: ✭ 49 (+113.04%)
ElasticFaceOfficial repository for ElasticFace: Elastic Margin Loss for Deep Face Recognition
Stars: ✭ 86 (+273.91%)
NoisyStudent"Self-training with Noisy Student improves ImageNet classification" pytorch implementation
Stars: ✭ 31 (+34.78%)
edge2viewThis is a pix2pix demo that learns from edge and translates this into view. A interactive application is also provided that translates edge to view.
Stars: ✭ 22 (-4.35%)
ConvLSTM-PyTorchConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
Stars: ✭ 202 (+778.26%)
DVAEOfficial implementation of Dynamical VAEs
Stars: ✭ 75 (+226.09%)
char-VAEInspired by the neural style algorithm in the computer vision field, we propose a high-level language model with the aim of adapting the linguistic style.
Stars: ✭ 18 (-21.74%)
swdunsupervised video and image generation
Stars: ✭ 50 (+117.39%)