RmdlRMDL: Random Multimodel Deep Learning for Classification
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Pytorch Kaldipytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
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Pytorch Pos TaggingA tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.
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ACTAlternative approach for Adaptive Computation Time in TensorFlow
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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).
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IseebetteriSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
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Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
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tiny-rnnLightweight C++11 library for building deep recurrent neural networks
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Rnn From ScratchUse tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs
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danifojo-2018-repeatrnnComparing Fixed and Adaptive Computation Time for Recurrent Neural Networks
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Rnn ctcRecurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
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RnnsharpRNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.
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Gru Svm[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection
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EasyesnPython library for Reservoir Computing using Echo State Networks
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Linear Attention Recurrent Neural NetworkA recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)
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Human-Activity-RecognitionHuman activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).
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VariationalNeuralAnnealingA variational implementation of classical and quantum annealing using recurrent neural networks for the purpose of solving optimization problems.
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DeepseqslamThe Official Deep Learning Framework for Route-based Place Recognition
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Codegan[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks
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Lstm Human Activity RecognitionHuman Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
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Theano Kaldi RnnTHEANO-KALDI-RNNs is a project implementing various Recurrent Neural Networks (RNNs) for RNN-HMM speech recognition. The Theano Code is coupled with the Kaldi decoder.
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Seq2seq ChatbotChatbot in 200 lines of code using TensorLayer
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sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
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sgrnnTensorflow implementation of Synthetic Gradient for RNN (LSTM)
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Dense BiLSTMTensorflow Implementation of Densely Connected Bidirectional LSTM with Applications to Sentence Classification
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Sequence-Models-courseraSequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.
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PFL-Non-IIDThe origin of the Non-IID phenomenon is the personalization of users, who generate the Non-IID data. With Non-IID (Not Independent and Identically Distributed) issues existing in the federated learning setting, a myriad of approaches has been proposed to crack this hard nut. In contrast, the personalized federated learning may take the advantage…
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altairAssessing Source Code Semantic Similarity with Unsupervised Learning
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rnn-from-scratchA Recurrent Neural Network implemented from scratch (using only numpy) in Python.
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nyyelppredicting yelp review rating using recurrent neural networks
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totally humansrnn trained on r/totallynotrobots 🤖
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deeptrolldetectorDeep troll uses a deep learning model that identifies whether an audio contains the Gemidao troll (AAAWN OOOWN NHAAA AWWWWN AAAAAH).
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OpenDialogAn Open-Source Package for Chinese Open-domain Conversational Chatbot (中文闲聊对话系统,一键部署微信闲聊机器人)
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Pytorch-POS-TaggerPart-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN
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ML2017FALLMachine Learning (EE 5184) in NTU
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DeepSentiPersRepository for the experiments described in the paper named "DeepSentiPers: Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus"
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rnn2dCPU and GPU implementations of some 2D RNN layers
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seeing-without-lookingPyTorch implementation for Seeing without Looking: Contextual Rescoring of Object Detections for AP Mazimization
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deep-improvisationEasy-to-use Deep LSTM Neural Network to generate song sounds like containing improvisation.
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fastmorphFast corpus search engine originally made for the Corpus of Written Tatar language
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dialogue-datasetscollect the open dialog corpus and some useful data processing utils.
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dtsA Keras library for multi-step time-series forecasting.
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Filipino-Text-BenchmarksOpen-source benchmark datasets and pretrained transformer models in the Filipino language.
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wordfish-pythonextract relationships from standardized terms from corpus of interest with deep learning 🐟
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question-pairA siamese LSTM to detect sentence/question pairs.
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