Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data.
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.
The inductive bias of a neural network is largely determined by the architecture and the training algorithm.
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.
The Neural-GC repository contains code for a deep learning-based approach to discovering Granger causality networks in multivariate time series.
This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.
AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks in PyTorch.
This repository contains code for the neural implicit reconstruction experiments in the paper Vector Neurons: A General Framework for SO(3)-Equivariant Networks.
This repository is the official PyTorch implementation of the paper ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction (2021)
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.
Ivy is a templated deep learning framework which maximizes the portability of deep learning codebases.
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 SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019).
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).
Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs.