34 Open source projects that are alternatives of or similar to large-scale-OT-mapping-TF

Unofficial PyTorch implementation of "GAN-QP: A Novel GAN Framework without Gradient Vanishing and Lipschitz Constraint"

TensorFlow implementation [ICLR 18] "Learning Approximate Inference Networks for Structured Prediction"

Learned string similarity for entity names using optimal transport.

6️⃣6️⃣6️⃣ Reproduce ICLR '18 under-reviewed paper "MULTI-TASK LEARNING ON MNIST IMAGE DATASETS"

Global NIPS Paper Implementation Challenge of "Hiding Images in Plain Sight: Deep Steganography"

Selective Classification For Deep Neural Networks.

Solve large instance of semi-discrete optimal transport problems and other Monge-Ampere equations

PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)

PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)

PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs

Continuous-time gradient flow for generative modeling and variational inference

Unofficial PyTorch implementation of "Progressive Growing of GANs for Improved Quality, Stability, and Variation".

Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in full in this ICML 2021 paper: https://arxiv.org/abs/2102.08622.

Code for NIPS 2017 learning to run challenge

A collection of AWESOME things about domian adaptation

Optimal transport algorithms for Julia

Code/Model release for NIPS 2017 paper "Attentional Pooling for Action Recognition"

Implementation of Dynamic Routing Between Capsules, Sara Sabour, Nicholas Frosst, Geoffrey E Hinton, NIPS 2017

Hiding Images within other images using Deep Learning

Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

Implementation for <Deep Hyperspherical Learning> in NIPS'17.

Code for "Effective Dimensionality Reduction for Word Embeddings".

Reason8.ai PyTorch solution for NIPS RL 2017 challenge

End-to-End Differentiable Proving

Structured Bayesian Pruning, NIPS 2017

Convolution dictionary learning for time-series

A state-of-the-art semi-supervised method for image recognition

Our NIPS 2017: Learning to Run source code

Implementation of the paper : "Toward Multimodal Image-to-Image Translation"

Binary Convolution Network for faster real-time processing in ASICs

Reproduction code for WGAN-LP

A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2017

Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"