Repository for the Model used in the publication 'Learning Atomic Multipoles: Prediction of the Electrostatic Potential with Equivariant Graph Neural Networks'. The model was trained on the following publicly available Dataset.
Check out the jupyter notebook for exemplary usecases. Versions used:
Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency (ICCV2021) Paper Link: https://arxiv.org/abs/2107.11355 This implementation bui
Traductor de señas Traductor de lengua de señas al español basado en Python con Opencv y MedaiPipe Requerimientos 🔧 Python 3.8 o inferior para evitar
DER.ClassIL.Pytorch This repo is the official implementation of DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR 2021)
GPRGNN This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network. Hidden state feature extraction i
Differentiable Surface Triangulation This is our implementation of the paper Differentiable Surface Triangulation that enables optimization for any pe
The Gluon API Specification The Gluon API specification is an effort to improve speed, flexibility, and accessibility of deep learning technology for
PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation The paper: https://arxiv.org/abs/1704.03296 What makes
Trimesh is a pure Python (2.7-3.4+) library for loading and using triangular meshes with an emphasis on watertight surfaces. The goal of the library i
yinyang A fuzzing framework for SMT solvers. Given a set of seed SMT formulas, yinyang generates mutant formulas to stress-test SMT solvers. yinyang c
AidForBlind Recommended PyCharm IDE Various Libraries used like OpenCV and other
AutoDSP TLDR; Train custom adaptive filter optimizers without hand tuning or extra labels. About Adaptive filtering algorithms are commonplace in sign
Feature Aggregation and Refinement Network for 2D Anatomical Landmark Detection Overview Localization of anatomical landmarks is essential for clinica
Big Vision This codebase is designed for training large-scale vision models on Cloud TPU VMs. It is based on Jax/Flax libraries, and uses tf.data and
EvoGAN an Evolutionary Algorithm assisted GAN ckpts
HEP Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior Implementation Python3 PyTorch=1.0 NVIDIA GPU+CUDA Training process The
Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm
cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.
Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil
One-shot Affordance Detection PyTorch implementation of our one-shot affordance detection models. This repository contains PyTorch evaluation code, tr
A project for counting vehicles using YOLOv4 + DeepSORT + Flask + Ngrok
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