Python Bayesian-neural-networks Resources

Sample-specific Bayesian Networks A framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample or per-patient re

This repository contains source code for the paper Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces a

Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems This repository is the official implementation of Rever

MedAI: Transparency in Medical Image Segmentation What is this repo This repo contains the code and experiments that are implemented to contribute in

HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty Giorgio Cantarini, Francesca Odone, Nicoletta Noceti, Federi

Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip) Introduction TL;DR: We propose an efficient and trainabl

Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil

Constructing Neural Network-Based Models for Simulating Dynamical Systems Note this repo is work in progress prior to reviewing This is a companion re

Dugh-NeurIPS-2021 This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroi

Generative Adversarial Networks(GANs) Vanilla GAN ClusterGAN Vanilla GAN Model Structure Final Generator Structure A MLP with 2 hidden layers of hidde

bayesmedaug: Bayesian Optimization Library for Medical Image Segmentation. bayesmedaug optimizes your data augmentation hyperparameters for medical im

Official repository of the paper (UAI 2021) "A Variational Approximation for Analyzing the Dynamics of Panel Data", Mixed Effect Neural ODE. Panel dat

Diverse Motion Stylization (Official) This is the official Pytorch implementation of this paper. Diverse Motion Stylization for Multiple Style Domains

MalanaNeuralNetwork Description Malware Analysis Neural Network project. Table of Contents Getting Started Requirements Installation Clone Set-Up VENV

Interesting and reproducible research works should be conserved. This repository wraps a collection of deep neural network models into a simple and un

Neural Nano-Optics for High-quality Thin Lens Imaging Project Page | Paper | Data Ethan Tseng, Shane Colburn, James Whitehead, Luocheng Huang, Seung-H

PonderNet-TensorFlow This is an Unofficial Implementation of the paper: PonderNet: Learning to Ponder in TensorFlow. Official PyTorch Implementation:

Contrastive Explanations for Model Interpretability This is the repository for the paper "Contrastive Explanations for Model Interpretability", about

DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng

A large-scale database for graph representation learning

Recaption Images with Generated Neural Image Caption Example Usage: Commandline: Recaption all images from folder /home/feng/Downloads/images to folde

UltraGCN This is our Pytorch implementation for our CIKM 2021 paper: Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. UltraGCN: A

Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks This repository contains the code and pre-trained

Targeted Neural Dynamical Modeling Note: This is a re-implementation (in Tensorflow2) of the original TNDM model. We do not plan to further update the

Wide-Networks This repository contains the code of various experiments on wide neural networks. In particular, we implement classes for abc-parameteri

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a

OnsagerNet Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks This is the original pyTorch implemenati

Face-Detection-with-MTCNN Face detection is a computer vision problem that involves finding faces in photos. It is a trivial problem for humans to sol

Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN) This is the implementation of the paper Multi-Age

The Network Simulator, Version 3 Table of Contents: An overview Building ns-3 Running ns-3 Getting access to the ns-3 documentation Working with the d

ParNet Custom Implementation of Non-deep Networks arXiv:2110.07641 Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun Official Repository https

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu, Qixuan Yu, Yang Zhang, S

Heterogeneous Temporal Graph Neural Network This repository contains the datasets and source code of HTGNN. run_mag.ipynb is the training and testing

Gradient representations in ReLU networks as similarity functions by Dániel Rácz and Bálint Daróczy. This repo contains the python code related to our

Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at

Meta-SparseINR Official PyTorch implementation of "Meta-learning Sparse Implicit Neural Representations" (NeurIPS 2021) by Jaeho Lee*, Jihoon Tack*, N

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated photonic circuit states under challenging physical constraints, then performs photonic core mapping via combined analytical solving and zeroth-order optimization.

ArSSR This repository is the pytorch implementation of our manuscript "An Arbitrary Scale Super-Resolution Approach for 3-Dimensional Magnetic Resonan

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The offical PyTorch implementation of Neural View Sy

Temporal-attentive-Covariance-Pooling-Networks-for-Video-Recognition This is an implementation of TCPNet. Introduction For video recognition task, a g

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal

SimplEx - Explaining Latent Representations with a Corpus of Examples Code Author: Jonathan Crabbé ([email protected]) This repository contains the imp

OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe

Dist2Dec: A Simplicial Neural Network for Homology Localization

RNN-Playwrite a reccurrent neural netowrk that when trained on a peice of text and fed a starting prompt will write its on 250 character text using LS

Number recognition Recognize numbers from a 28 x 28 image using neural networks Usage This is an example of a simple usage of number-recognition NOTE:

With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.

Video Matting via Consistency-Regularized Graph Neural Networks Project Page | Real Data | Paper Installation Our code has been tested on Python 3.7,

Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati

Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021) Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu This is the officia

ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica

Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio

mito-network-sharing Sharing of contents on mitochondrial encounter networks Required: R with igraph, brainGraph, ggplot2, and XML libraries; igraph l

Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.

This repository contains the Matlab implementations for the following multi-target filtering/tracking algorithms: - Folder PMBM contains the implemen

NeRV: Neural Representations for Videos (NeurIPS 2021) Project Page | Paper | UVG Data Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav S

Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th

Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie

NeRV: Neural Representations for Videos (NeurIPS 2021) Project Page | Paper | UVG Data Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav S

NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti

Layered Neural Atlases for Consistent Video Editing Project Page | Paper This repository contains an implementation for the SIGGRAPH Asia 2021 paper L

Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con

A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.

Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+

A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G

Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson

handwritten-digits-recognition A script that trains a model to recognize handwritten digits using the MNIST data set. Then it loads external files and

DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im

ConformalLayers: A non-linear sequential neural network with associative layers ConformalLayers is a conformal embedding of sequential layers of Convo

NAS-FCOS: Fast Neural Architecture Search for Object Detection This project hosts the train and inference code with pretrained model for implementing

EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud

HMemNetworks Code and documentation for Harmonic Memory Networks, a series of models for compositionally assembling representations of graph elements

CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k

DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using

Zoobot Zoobot classifies galaxy morphology with deep learning. This code will let you: Reproduce and improve the Galaxy Zoo DECaLS automated classific

Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi

arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro

CUP-DNN CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary. The model was trained on the expre

CBREN This is the Pytorch implementation for our IEEE TCSVT paper : CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhanceme

A PyTorch-based library for fast prototyping and sharing of deep neural network models.

Bayesian Optimisation Research This directory contains official implementations for Bayesian optimisation works developped by Huawei R&D, Noah's Ark L

Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train

Attentive Implicit Representation Networks (AIR-Nets) Preprint | Supplementary | Accepted at the International Conference on 3D Vision (3DV) teaser.mo

Mutli-agent task allocation This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams. To change

Machine Learning Sleep Schedule Tracker What is it? Convolutional neural network web app trained to track our infant’s sleep schedule using our Google

RLA-Net: Recurrent Layer Aggregation Recurrence along Depth: Deep Networks with Recurrent Layer Aggregation This is an implementation of RLA-Net (acce

Attentive Implicit Representation Networks (AIR-Nets) Preprint | Supplementary | Accepted at the International Conference on 3D Vision (3DV) teaser.mo

Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to

Overview This code provides various models combining dilated convolutions with residual networks. Our models can achieve better performance with less

PyTorch implementation of Convolutional Neural Fabrics arxiv:1606.02492 There are some minor differences: The raw image is first convolved, to obtain

pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo

Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l

DiracNets v2 update (January 2018): The code was updated for DiracNets-v2 in which we removed NCReLU by adding per-channel a and b multipliers without

Box Convolution Layer for ConvNets Single-box-conv network (from `examples/mnist.py`) learns patterns on MNIST What This Is This is a PyTorch implemen

octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa

MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f

LegoNet This code is the implementation of ICML2019 paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters Run python train.py You c

Point-Based Modeling of Human Clothing Paper | Project page | Video This is an official PyTorch code repository of the paper "Point-Based Modeling of