22 Repositories
Python smooth-grad Libraries
📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.
Explainable CNNs 📦 Flexible visualization package for generating layer-wise explanations for CNNs. It is a common notion that a Deep Learning model i
Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.
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
PyTorch reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].
Smooth ReLU in PyTorch Unofficial PyTorch reimplementation of the Smooth ReLU (SmeLU) activation function proposed in the paper Real World Large Scale
Optimizing synthesizer parameters using gradient approximation
Optimizing synthesizer parameters using gradient approximation NASH 2021 Hackathon! These are some experiments I conducted during NASH 2021, the Neura
Official implementation for the paper: Generating Smooth Pose Sequences for Diverse Human Motion Prediction
Generating Smooth Pose Sequences for Diverse Human Motion Prediction This is official implementation for the paper Generating Smooth Pose Sequences fo
An assignment from my grad-level data mining course demonstrating some experience with NLP/neural networks/Pytorch
NLP-Pytorch-Assignment An assignment from my grad-level data mining course (before I started personal projects) demonstrating some experience with NLP
A smooth and powerful Telegram Userbot made to make Telegram easier.
| Xᴇɴᴏ Bᴏᴛ Is One Of The Fastest & Smoothest Bot On Telegram Based on Telethon|
A Pytorch implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU_pytorch A Pytorch Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/ab
Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption
SG-GAN TensorFlow implementation of SG-GAN. Prerequisites TensorFlow (implemented in v1.3) numpy scipy pillow Getting Started Train Prepare dataset. W
Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU A Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/abs/211
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
TorchCAM: class activation explorer Simple way to leverage the class-specific activation of convolutional layers in PyTorch. Quick Tour Setting your C
A repository of links with advice related to grad school applications, research, phd etc
A repository of links with advice related to grad school applications, research, phd etc
Pytorch implementation of convolutional neural network visualization techniques
Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.
Silky smooth profiling for Django
Silk Silk is a live profiling and inspection tool for the Django framework. Silk intercepts and stores HTTP requests and database queries before prese
Silky smooth profiling for Django
Silk Silk is a live profiling and inspection tool for the Django framework. Silk intercepts and stores HTTP requests and database queries before prese
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Tested on many Common CNN Networks and Vision Transformers. ⭐ Includes smoo
Neural network visualization toolkit for tf.keras
Neural network visualization toolkit for tf.keras
Callable PyTrees and filtered JIT/grad transformations = neural networks in JAX.
Equinox Callable PyTrees and filtered JIT/grad transformations = neural networks in JAX Equinox brings more power to your model building in JAX. Repr
Pytorch implementation of "Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech"
GradTTS Unofficial Pytorch implementation of "Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech" (arxiv) About this repo This is an unoffic
This code extends the neural style transfer image processing technique to video by generating smooth transitions between several reference style images
Neural Style Transfer Transition Video Processing By Brycen Westgarth and Tristan Jogminas Description This code extends the neural style transfer ima
Silky smooth profiling for Django
Silk Silk is a live profiling and inspection tool for the Django framework. Silk intercepts and stores HTTP requests and database queries before prese