Convolution dictionary learning for time-series
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Updated
May 20, 2023 - Python
Convolution dictionary learning for time-series
Our NIPS 2017: Learning to Run source code
Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"
Code for "Effective Dimensionality Reduction for Word Embeddings".
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
A state-of-the-art semi-supervised method for image recognition
Simple & Effective Dimensionality Reduction for Word Embeddings. Presented at NIPS 2017 LLLD & RepL4NLP 2019 Workshop.
Reason8.ai PyTorch solution for NIPS RL 2017 challenge
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
Tensorflow Implementation of "Large-scale Optimal Transport and Mapping Estimation"(ICLR2018/NIPS 2017 OTML)
Chainer implementation of the paper "Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results" (https://arxiv.org/abs/1703.01780)
Code/Model release for NIPS 2017 paper "Attentional Pooling for Action Recognition"
Implementation for <Deep Hyperspherical Learning> in NIPS'17.
PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)
text convolution-deconvolution auto-encoder model in PyTorch
Implementation of the paper : "Toward Multimodal Image-to-Image Translation"
Fast-Slow Recurrent Neural Networks
Tensorflow Implementation of adversarial learning based adversarial example generator
Z-Forcing: Training Stochastic Recurrent Networks for Speech Modelling
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