Code from the NNFS book (https://nnfs.io) separated by chapter. The NNFS book is written with the Python programming lanauge. If you're interested in seeing this same content, but with 40+ other programming languages, check out: https://github.com/sentdex/nnfsix
MSc Dissertation Code ReadMe Sector Volatility Prediction Performance Using GARCH Models and Artificial Neural Networks Curtis Nybo MSc Quantitative F
QAConv Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting This PyTorch code is proposed in
TimeSHAP TimeSHAP is a model-agnostic, recurrent explainer that builds upon KernelSHAP and extends it to the sequential domain. TimeSHAP computes even
Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing
Joint Channel and Weight Pruning for Model Acceleration on Mobile Devices Abstract For practical deep neural network design on mobile devices, it is e
This repository contains the implementation for the paper Information Theoretic StructuredGenerative Modeling, Specially thanks for the open-source co
Learning to Stylize Novel Views [Project] [Paper] Contact: Hsin-Ping Huang ([ema
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations This repo contains the Pytorch implementation of our paper: Revisit
Layer-wise Relevance Propagation (LRP) in PyTorch Basic unsupervised implementation of Layer-wise Relevance Propagation (Bach et al., Montavon et al.)
WGAN-GP An pytorch implementation of Paper "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, SciPy, Matplotlib A recent NVIDIA GPU
Face Recognition Using Pytorch Python 3.7 3.6 3.5 Status This is a repository for Inception Resnet (V1) models in pytorch, pretrained on VGGFace2 and
Progressive Coordinate Transforms for Monocular 3D Object Detection This repository is the official implementation of PCT. Introduction In this paper,
BABEL is a large dataset with language labels describing the actions being performed in mocap sequences. BABEL labels about 43 hours of mocap sequences from AMASS [1] with action labels.
Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berke
3D-GMPDCNN Geological Modeling Using 3D Pixel-Adaptive and Deformable Convolutional Neural Network PyTorch implementation of "Geological Modeling Usin
Perspective: Julia for Biologists 1. Examples Speed: Example 1 - Single cell data and network inference Domain: Single cell data Methodology: Network
Constrained Language Models Yield Few-Shot Semantic Parsers This repository contains tools and instructions for reproducing the experiments in the pap
RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc
PyTorch Implementation of EigenGAN Train python train.py [image_folder_path] --name [experiment name] Test python test.py [ckpt path] --traverse FFH
PlantDoc: A Dataset for Visual Plant Disease Detection This repository contains the Cropped-PlantDoc dataset used for benchmarking classification mode
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