Python Bayesian-networks Resources

Focal Sparse Convolutional Networks for 3D Object Detection (CVPR 2022, Oral) This is the official implementation of Focals Conv (CVPR 2022), a new sp

Description Killing features Perform a large-scale scans using Nmap! Allows you to use Masscan to scan targets and execute Nmap on detected ports with

What is judgyprophet? judgyprophet is a Bayesian forecasting algorithm based on Prophet, that enables forecasting while using information known by the

RCIL [CVPR2022] Representation Compensation Networks for Continual Semantic Segmentation Chang-Bin Zhang1, Jia-Wen Xiao1, Xialei Liu1, Ying-Cong Chen2

KFAC-JAX - Second Order Optimization with Approximate Curvature in JAX Installation | Quickstart | Documentation | Examples | Citing KFAC-JAX KFAC-JAX

Convolutional Dynamic Alignment Networks for Interpretable Classifications M. Böhle, M. Fritz, B. Schiele. B-cos Networks: Alignment is All we Need fo

GULAG: GUessing LAnGuages with neural networks Classify languages in text via neural networks. Привет! My name is Egor. Was für ein herrliches Frühl

Visual Transformer for Facial Emotion Recognition (FER) This project has the aim to build an efficient Visual Transformer for the Facial Emotion Recog

Multi-Graph Fusion Networks for Urban Region Embedding (IJCAI-22) This is the implementation of Multi-Graph Fusion Networks for Urban Region Embedding

Graph Stochastic Attention (GSAT) The official implementation of GSAT for our paper: Interpretable and Generalizable Graph Learning via Stochastic Att

SignLangGNN When GNNs 💜 MediaPipe. This is a starter project where I tried to implement some traditional image classification problem i.e. the ASL si

Intrusion-Detection-System-Using-CNN-and-Transfer-Learning This is the code for the paper entitled "A Transfer Learning and Optimized CNN Based Intrus

Description This repository contains code accompanying the following paper on the Make-It robotic flow chemistry platform developed by the Jensen Rese

GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation [OpenReview] [arXiv] [Code] The official implementation of GeoDiff: A Geome

Understanding Bayesian Classification This repository hosts the code to reproduce the results presented in the paper On Uncertainty, Tempering, and Da

F8Net Fixed-Point 8-bit Only Multiplication for Network Quantization (ICLR 2022 Oral) OpenReview | arXiv | PDF | Model Zoo | BibTex PyTorch implementa

Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis Multi-View Consistent Generative Adversarial Networks for 3D-aware

Learn Deep Learning with AI Summer A collection of all articles (almost 100) written for the AI Summer blog organized by topic. Deep Learning Theory M

Machine Learning With Python Get started with Machine Learning with Python An engaging introduction to Machine Learning with Python TL;DR Download all

PyGOD is a Python library for graph outlier detection (anomaly detection). This exciting yet challenging field has many key applications, e.g., detect

YOLO-V5 GRADCAM I constantly desired to know to which part of an object the object-detection models pay more attention. So I searched for it, but I di

Traffic-Sign-Recognition In this report, we propose a Convolutional Neural Network(CNN) for traffic sign classification that achieves outstanding perf

ConvNeXt-TF This repository provides TensorFlow / Keras implementations of different ConvNeXt [1] variants. It also provides the TensorFlow / Keras mo

VQGAN-CLIP-GENERATOR Overview This is a package (with available notebook) for running VQGAN+CLIP locally, with a focus on ease of use, good documentat

DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Abstract: Adversarial training has been proven to

Potato Disease Classification Setup for Python: Install Python (Setup instructions) Install Python packages pip3 install -r training/requirements.txt

Who has never met a forged picture on the web ? No one ! Everyday we are constantly facing fake pictures touched up in Photoshop but it is not always

Research on Tabular Deep Learning For paper implementations, see the section "Papers and projects". rtdl is a PyTorch-based package providing a user-f

Eigenlearning This repo contains code for replicating the experiments of the paper A Theory of the Inductive Bias and Generalization of Kernel Regress

Finite basis physics-informed neural networks (FBPINNs) This repository reproduces the results of the paper Finite Basis Physics-Informed Neural Netwo

DeepXF: Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor Model Also, verify TS signal similarities

Bitcoin Realized Volatility Forecasting with GARCH and Multivariate LSTM Author: Chi Bui This Repository Repository Directory ├── README.md

Documents: https://pytoydl.readthedocs.io/zh/latest/ Pytoydl A toy deep learning framework built upon numpy. You can star this repository to keep trac

Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of given options.

Prisma Cloud CLI The Prisma Cloud CLI is a command line interface for Prisma Cloud by Palo Alto Networks. Support This project has been developed by P

APP: Anytime Progressive Pruning Diganta Misra1,2,3, Bharat Runwal2,4, Tianlong Chen5, Zhangyang Wang5, Irina Rish1,3 1 Mila - Quebec AI Institute,2 L

hyperbox-brain is a Python open source toolbox implementing hyperbox-based machine learning algorithms built on top of scikit-learn and is distributed

A variational Bayesian method for similarity learning in non-rigid image registration We provide the source code and the trained models used in the re

Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, “Improving evidential deep learning via multi-task le

On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks We provide the code (in PyTorch) and datasets for our paper "On Size-Orient

Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d

DiffGAN-TTS - PyTorch Implementation PyTorch implementation of DiffGAN-TTS: High

DIGAN (ICLR 2022) Official PyTorch implementation of "Generating Videos with Dyn

COMP-445 Data Communications & Computer Networks Change Python version in Conda

Lightweight (Bayesian) Media Mix Model This is not an official Google product. L

Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical V

B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search This is the offical implementation of the

Hyper-Convolution Networks for Biomedical Image Segmentation Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentatio

AllSet This is the repo for our paper: You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks. We prepared all codes and a subse

Learning Synthetic Environments and Reward Networks for Reinforcement Learning We explore meta-learning agent-agnostic neural Synthetic Environments (

The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks This folder contains the code to reproduce the data in "The Implicit Bias o

MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi

TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular

Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe

OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.

C-CNN: Contourlet Convolutional Neural Networks This repo implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networ

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

Julia package for contraction of tensor networks, based on the sweep line algorithm outlined in the paper General tensor network decoding of 2D Pauli codes

Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.

Fortuitous Forgetting in Connectionist Networks Introduction This repository includes reference code for the paper Fortuitous Forgetting in Connection

Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp

This package requires jax, tensorflow, and numpy. Either tensorflow or scikit-learn can be used for loading data. To run in a nix-shell with required

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern

Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces" This repo contains the implementation of GEBO algorithm.

Posterior temperature optimized Bayesian models for inverse problems in medical imaging Max-Heinrich Laves*, Malte Tölle*, Alexander Schlaefer, Sandy

A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.

FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Under construction. Description Code for Phase diagram of S

Official Code for the Paper "Transformers Can Do Bayesian Inference" We train Transformers to do Bayesian Prediction on novel datasets for a large var

DiffStride is a pooling layer with learnable strides. Unlike strided convolutions, average pooling or max-pooling that require cross-validating stride values at each layer, DiffStride can be initialized with an arbitrary value at each layer (e.g. (2, 2) and during training its strides will be optimized for the task at hand.

Overview Code and supplemental materials for Karduni et al., 2020 IEEE Vis. "A Bayesian cognition approach for belief updating of correlation judgemen

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.

Network tests automation Network tests automation About this repository Requirements Requirements on your laptop Requirements on the switches Quick te

This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015

This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle

AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin

pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D

pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i

Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!

keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o

Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

DIR-GNN "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in

NLP - Movie review sentiment analysis The colab notebook contains the code for building a LSTM Recurrent Neural Network that gives 87-88% accuracy on

1st place solution in CCF BDCI 2021 ULSEG challenge This is the source code of the 1st place solution for ultrasound image angioma segmentation task (

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set This is the repository for the Deep Learning proje

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap

Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill This is a port of the amazing openskill.js package

Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce

CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels Accurate pressure drop estimat

Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth [Paper] Downloads [Downloads] Trained ckpt files for NYU Depth V2 and

Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges