Code implementation for the paper 'Conditional Gaussian PAC-Bayes'.

Overview

CondGauss

This repository contains PyTorch code for the paper Stochastic Gaussian PAC-Bayes.

A novel PAC-Bayesian training method is implemented.

There are a few examples of how to run the code in the main.py script.

For any question, feel free to contact me.

Zero-Cost Proxies for Lightweight NAS

Zero-Cost-NAS Companion code for the ICLR2021 paper: Zero-Cost Proxies for Lightweight NAS tl;dr A single minibatch of data is used to score neural ne

SamsungLabs 108 Dec 20, 2022
LaneAF: Robust Multi-Lane Detection with Affinity Fields

LaneAF: Robust Multi-Lane Detection with Affinity Fields This repository contains Pytorch code for training and testing LaneAF lane detection models i

155 Dec 17, 2022
Opinionated code formatter, just like Python's black code formatter but for Beancount

beancount-black Opinionated code formatter, just like Python's black code formatter but for Beancount Try it out online here Features MIT licensed - b

Launch Platform 16 Oct 11, 2022
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes

Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes [Paper] Method overview 4DMatch Benchmark 4DMatch is a benchmark for matc

103 Jan 06, 2023
A PyTorch implementation of the Transformer model in "Attention is All You Need".

Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V

Yu-Hsiang Huang 7.1k Jan 04, 2023
A Framework for Encrypted Machine Learning in TensorFlow

TF Encrypted is a framework for encrypted machine learning in TensorFlow. It looks and feels like TensorFlow, taking advantage of the ease-of-use of t

TF Encrypted 0 Jul 06, 2022
Improving Calibration for Long-Tailed Recognition (CVPR2021)

MiSLAS Improving Calibration for Long-Tailed Recognition Authors: Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia [arXiv] [slide] [BibTeX] Introductio

DV Lab 116 Dec 20, 2022
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.

mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.

Katsuya Hyodo 24 Mar 02, 2022
This is the code for HOI Transformer

HOI Transformer Code for CVPR 2021 accepted paper End-to-End Human Object Interaction Detection with HOI Transformer. Reproduction We recomend you to

BigBangEpoch 124 Dec 29, 2022
Code and data (Incidents Dataset) for ECCV 2020 Paper "Detecting natural disasters, damage, and incidents in the wild".

Incidents Dataset See the following pages for more details: Project page: IncidentsDataset.csail.mit.edu. ECCV 2020 Paper "Detecting natural disasters

Ethan Weber 67 Dec 27, 2022
Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

Clara Meister 50 Nov 12, 2022
This repository contains a CBIR system that uses swin transformer to extract image's feature.

Swin-transformer based CBIR This repository contains a CBIR(content-based image retrieval) system. Here we use Swin-transformer to extract query image

JsHou 12 Nov 17, 2022
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search DropNAS, a grouped operation dropout method for one-level DARTS, with better

weijunhong 4 Aug 15, 2022
Code To Tune or Not To Tune? Zero-shot Models for Legal Case Entailment.

COLIEE 2021 - task 2: Legal Case Entailment This repository contains the code to reproduce NeuralMind's submissions to COLIEE 2021 presented in the pa

NeuralMind 13 Dec 16, 2022
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

Fuhang 5 Jan 18, 2022
A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.

DrQA A pytorch implementation of the ACL 2017 paper Reading Wikipedia to Answer Open-Domain Questions (DrQA). Reading comprehension is a task to produ

Runqi Yang 394 Nov 08, 2022
Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation (NeurIPS 2021) Code for our NeurIPS 2021 paper 'Exploiting the Intri

Shiqi Yang 53 Dec 25, 2022
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

Scripts for "Current best-practices in single-cell RNA-seq: a tutorial" This repository is complementary to the publication: M.D. Luecken, F.J. Theis,

Theis Lab 968 Dec 28, 2022
Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".

AST: Audio Spectrogram Transformer Introduction Citing Getting Started ESC-50 Recipe Speechcommands Recipe AudioSet Recipe Pretrained Models Contact I

Yuan Gong 603 Jan 07, 2023
Accelerated NLP pipelines for fast inference on CPU and GPU. Built with Transformers, Optimum and ONNX Runtime.

Optimum Transformers Accelerated NLP pipelines for fast inference 🚀 on CPU and GPU. Built with 🤗 Transformers, Optimum and ONNX runtime. Installatio

Aleksey Korshuk 115 Dec 16, 2022