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Evaluation framework for digital neuromorphic architectures
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
[NeurIPS 2022] Online Training Through Time for Spiking Neural Networks
Update arXiv papers about Spiking Neural Networks daily.
snu-ccl / FHE-MP-CNN
Forked from microsoft/SEALImplementation of deep ResNet model on CKKS scheme in Microsoft SEAL library using multiplexed parallel convolution
HElib is an open-source software library that implements homomorphic encryption. It supports the BGV scheme with bootstrapping and the Approximate Number CKKS scheme. HElib also includes optimizati…
This is the documentation of the 5 day workshop "Advanced Physical Design using OpenLANE/Sky130" by VLSI System Design (VSD) that was carried out from 04/07/2021 to 04/11/2021.
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Updated Dec 6, 2022
A repository of a paper named "Can We Use Diffusion Probabilistic Models for 3D Motion Prediction?", accepted to ICRA 2023.
OpenMMLab Pre-training Toolbox and Benchmark
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.
This is the development repository for the OpenFHE library. The current (stable) version is v1.2.0 (released on June 25, 2024).
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Let's train vision transformers (ViT) for cifar 10!
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Quantization of Convolutional Neural networks.
Implementation for Non-Uniform Step Size Quantization for Accurate Post-Training Quantization (ECCV 2022)
Pretrained TorchVision models on CIFAR10 dataset (with weights)
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Code for reproducing Manifold Mixup results (ICML 2019)
A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
Pytorch implementation of various Knowledge Distillation (KD) methods.
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
Script to typecast ONNX model parameters from INT64 to INT32.