Differentiable architecture search for convolutional and recurrent networks
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Updated
Jan 3, 2021 - Python
Differentiable architecture search for convolutional and recurrent networks
Implementing Recurrent Neural Network from Scratch
A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.
🔬 Nano size Theano LSTM module
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences (NIPS 2016) - Tensorflow 1.0
Implementation of the paper Recurrent Independent Mechanisms (https://arxiv.org/pdf/1909.10893.pdf)
Music genre classification model using CRNN
Implementation/simulation of the predictive forward-forward credit assignment algorithm for training neurobiologically-plausible recurrent neural network models.
Implementation of Griffin from the paper: "Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models"
RAN: Recurrent Attention Networks for Long-text Modeling | Findings of ACL23
Source code of "Scalable Recurrent Neural Network for Hyperspectral Image Classification"
A simpler Pytorch + Zeta Implementation of the paper: "SiMBA: Simplified Mamba-based Architecture for Vision and Multivariate Time series"
Sentence Sentiment Analysis
Collection of malware detection models using time series data.
Transformer Architectures Comparison in Natural Language Generation Tasks
using encoder decoder neural net architecture to translate french to english
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