PyTorch and TensorFlow implementation of NCP, LTC, and CfC wired neural models
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Updated
Aug 14, 2024 - Python
PyTorch and TensorFlow implementation of NCP, LTC, and CfC wired neural models
🌊 Numerically solving and backpropagating through the wave equation
Implementation of Vision Mamba from the paper: "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" It's 2.8x faster than DeiT and saves 86.8% GPU memory when performing batch inference to extract features on high-res images
Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.
用Tensorflow实现的深度神经网络。
[IEEE TGRS 2020] Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network
Official PyTorch code for "Recurrent Off-policy Baselines for Memory-based Continuous Control" (DeepRL Workshop, NeurIPS 21)
Time series forecasting
⚡ Create handwritten documents from text with a Neural Network!
Implementation of Liquid Nets in Pytorch
A Novel Approach to Video Super-Resolution using Frame Recurrence and Generative Adversarial Networks | Python3 | PyTorch | OpenCV2 | GANs | CNNs
[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset
Character Embeddings Recurrent Neural Network Text Generation Models
Estimate intrinsic Permanent Magnet Synchronous Motor temperatures with deep recurrent and convolutional neural networks.
A Language Classifier powered by Recurrent Neural Network implemented in Python without AI libraries. AI from scratch.
Pytorch implementation for 'Interactive Reconstruction of Monte Carlo Image Sequences using a Recurrent Denoising Autoencoder' , https://research.nvidia.com/publication/interactive-reconstruction-monte-carlo-image-sequences-using-recurrent-denoising
A Python library for Continual Inference Networks in PyTorch
Official code for Coupled Oscillatory RNN (ICLR 2021, Oral)
PyTorch based autoencoder for sequential data
Sequence-to-sequence autoencoder for unsupervised learning of nonlinear dynamics (Tensorflow).
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