Python Transporter-nets Resources

Intro to Deep Learning Materials are part of North South University (NSU) Intro to Deep Learning with PyTorch workshop series. (Slides) Related materi

Disentangled Representation Learning for Text-Video Retrieval This is a PyTorch implementation of the paper Disentangled Representation Learning for T

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

Real Cascade U-Nets for Anime Image Super Resolution 中文 | English 🔥 Real-CUGAN

GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit

This folder contains the code for 'Scalable Variational Approaches for Bayesian Causal Discovery'. Installation To install, use conda with conda env c

MOVED TO HERE Spatial Transformer Networks Spatial Transformer Networks (STN) is a dynamic mechanism that produces transformations of input images (or

Hierarchical Attentive Recurrent Tracking This is an official Tensorflow implementation of single object tracking in videos by using hierarchical atte

SeqGAN Requirements: Tensorflow r1.0.1 Python 2.7 CUDA 7.5+ (For GPU) Introduction Apply Generative Adversarial Nets to generating sequences of discre

Status: Archive (code is provided as-is, no updates expected) InfoGAN Code for reproducing key results in the paper InfoGAN: Interpretable Representat

pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a

[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets Introduction This repo contains the source code accompanying the paper: Well-tuned Sim

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

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

Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for

TOQ-Nets-PyTorch-Release Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets). Temporal and Object Quantification Net

NudeNet: Neural Nets for Nudity Classification, Detection and selective censoring Uncensored version of the following image can be found at https://i.

ReLU-GP Residual (RGPR) This repository contains code for reproducing the following NeurIPS 2021 paper: @inproceedings{kristiadi2021infinite, title=

Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for

Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer

Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer

SMD-Nets: Stereo Mixture Density Networks This repository contains a Pytorch implementation of "SMD-Nets: Stereo Mixture Density Networks" (CVPR 2021)

Endocv2021-winner [Paper] This is the winning solution of the Endocv-2021 grand challange. Dependencies pytorch # tested with 1.7 and 1.8 torchvision

What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space Introduction: Environment: Python3.6.5, PyTorch1.5.0 Dataset: CIFAR-10, Image

Investigating U-NETS With Various Intermediate Blocks For Spectrogram-based Singing Voice Separation A Pytorch Implementation of the paper "Investigat

Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components

Ravens is a collection of simulated tasks in PyBullet for learning vision-based robotic manipulation, with emphasis on pick and place. It features a Gym-like API with 10 tabletop rearrangement tasks, each with (i) a scripted oracle that provides expert demonstrations (for imitation learning), and (ii) reward functions that provide partial credit (for reinforcement learning).

Animating the Optimization Trajectory of Neural Nets loss-landscape-anim lets you create animated optimization path in a 2D slice of the loss landscap