DartsDifferentiable architecture search for convolutional and recurrent networks
Stars: ✭ 3,463 (+16390.48%)
Mutual labels: language-modeling, neural-architecture-search
DeepSegmentorSequence Segmentation using Joint RNN and Structured Prediction Models (ICASSP 2017)
Stars: ✭ 17 (-19.05%)
Mutual labels: recurrent-neural-networks
datastories-semeval2017-task6Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
Stars: ✭ 20 (-4.76%)
Mutual labels: recurrent-neural-networks
deepblastNeural Networks for Protein Sequence Alignment
Stars: ✭ 29 (+38.1%)
Mutual labels: language-modeling
BossNAS(ICCV 2021) BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search
Stars: ✭ 125 (+495.24%)
Mutual labels: neural-architecture-search
codeprepA toolkit for pre-processing large source code corpora
Stars: ✭ 39 (+85.71%)
Mutual labels: language-modeling
referit3dCode accompanying our ECCV-2020 paper on 3D Neural Listeners.
Stars: ✭ 59 (+180.95%)
Mutual labels: language-modeling
course-content-dlNMA deep learning course
Stars: ✭ 537 (+2457.14%)
Mutual labels: recurrent-neural-networks
lingua-go👄 The most accurate natural language detection library for Go, suitable for long and short text alike
Stars: ✭ 684 (+3157.14%)
Mutual labels: language-modeling
SpeakerDiarization RNN CNN LSTMSpeaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).
Stars: ✭ 56 (+166.67%)
Mutual labels: recurrent-neural-networks
TF-NASTF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search (ECCV2020)
Stars: ✭ 66 (+214.29%)
Mutual labels: neural-architecture-search
mindwareAn efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Stars: ✭ 34 (+61.9%)
Mutual labels: neural-architecture-search
entity-networkTensorflow implementation of "Tracking the World State with Recurrent Entity Networks" [https://arxiv.org/abs/1612.03969] by Henaff, Weston, Szlam, Bordes, and LeCun.
Stars: ✭ 58 (+176.19%)
Mutual labels: recurrent-neural-networks
deep-learningAssignmends done for Udacity's Deep Learning MOOC with Vincent Vanhoucke
Stars: ✭ 94 (+347.62%)
Mutual labels: recurrent-neural-networks
sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
Stars: ✭ 28 (+33.33%)
Mutual labels: recurrent-neural-networks
Water-classifier-fastaiDeploy your Flask web app classifier on Heroku which is written using fastai library.
Stars: ✭ 37 (+76.19%)
Mutual labels: fastai
regulatory-predictionCode and Data to accompany "Dilated Convolutions for Modeling Long-Distance Genomic Dependencies", presented at the ICML 2017 Workshop on Computational Biology
Stars: ✭ 26 (+23.81%)
Mutual labels: recurrent-neural-networks
NeuroAINeuroAI-UW seminar, a regular weekly seminar for the UW community, organized by NeuroAI Shlizerman Lab.
Stars: ✭ 36 (+71.43%)
Mutual labels: recurrent-neural-networks