## Pytorch implementation of the Variational Recurrent Neural Network

Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data.

Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data.

A PyTorch Implementation of Neural IMage Assessment

PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing.

This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN)

The point of the paper is to execute some common image manipulation tasks using neural networks untrained on data prior to use.

NMN is a network that is assembled dynamically by composing shallow network fragments called modules into a deeper structure.

Image restoration with neural networks but without learning

The inductive bias of a neural network is largely determined by the architecture and the training algorithm.

Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch.

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch

This repository contains the code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty.

Neural Ensemble Search for Performant and Calibrated Predictions

EPSANetï¼šAn Efficient Pyramid Split Attention Block on Convolutional Neural Network

NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination

small collection of functions for neural networks.

The Neural-GC repository contains code for a deep learning-based approach to discovering Granger causality networks in multivariate time series.

A supplementary code for Editable Neural Networks, an ICLR 2020 submission by Anton Sinitsin

Geometry-Aware Gradient Algorithms for Neural Architecture Search.

Official code for "Mean Shift for Self-Supervised Learning"

This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.

All of the course materials for the Zero to Mastery Deep Learning with TensorFlow course.

This is the repository for the collection of Graph Neural Network for Traffic Forecasting.

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery

Speeding up Neural Radiance Fields with Thousands of Tiny MLPs.

AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks in PyTorch.

Portal is the fastest way to load and visualize your deep neural networks on images and videos

This repository contains code for the neural implicit reconstruction experiments in the paper Vector Neurons: A General Framework for SO(3)-Equivariant Networks.

An end-to-end machine learning library to directly optimize AUC (AUROC, AUPRC) loss

This repository is the official PyTorch implementation of the paper ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction (2021)

Self-training with Weak Supervision (NAACL 2021)

Expressive Power of Invariant and Equivariant Graph Neural Networks

Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

This repository contains the code release for Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields.

Neural Fixed-Point Acceleration for SCS

Ivy is a templated deep learning framework which maximizes the portability of deep learning codebases.

TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020)

A multistream CNN is a novel neural network architecture for robust acoustic modeling in speech recognition tasks.

Perturbative Neural Networks (PNN) This is an attempt to reproduce results in Perturbative Neural Networks paper. See original repo for details. Motivation The original implementation used regular convolutions in the first layer, and

A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019).

A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019).

Code for visualizing the loss landscape of neural nets

This repo contains a PyTorch implementation of a character-level convolutional neural network for text classification.

DiffAI is a system for training neural networks to be provably robust and for proving that they are robust.

A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019).

Accelerating Fluid Simulation with Convolutional Neural Networks. A PyTorch/ATen Implementation.

A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)

Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs.

NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) in Python using Pytorch.

Finite difference solution of 2D Poisson equation