Python/Rust implementations and notes from Proofs Arguments and Zero Knowledge

Last update: Jan 04, 2023

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Overview

What is this?

This is where I'll be collecting resources related to the Study Group on Dr. Justin Thaler's Proofs Arguments And Zero Knowledge Book. The notes posted here will be copied out of my personal Obsidian note client; certain features like image and latex embedding will not render on Github, though should still be readable. If you would like to read them with latex rendering, a hack solution might be to copy them to a HackMD document.

The group open to everyone, and runs out of the ZK hack discord server by myself and the nice folks at the Zero Knowledge Podcast.

Have a nice repo of your own? I'd love to link to it! Questions about this resource? DM me on Twitter.

Owner

Thor

zk wink

GitHub Repository

CRNN With PyTorch

CRNN-PyTorch Implementation of https://arxiv.org/abs/1507.05717

4 Sep 01, 2022

AAAI-22 paper: SimSR: Simple Distance-based State Representationfor Deep Reinforcement Learning

SimSR Code and dataset for the paper SimSR: Simple Distance-based State Representationfor Deep Reinforcement Learning (AAAI-22). Requirements We assum

7 Dec 19, 2022

I decide to sync up this repo and self-critical.pytorch. (The old master is in old master branch for archive)

An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin

1.3k Dec 31, 2022

Learning Optical Flow from a Few Matches (CVPR 2021)

Learning Optical Flow from a Few Matches This repository contains the source code for our paper: Learning Optical Flow from a Few Matches CVPR 2021 Sh

159 Dec 16, 2022

Pytorch implementation of MalConv

MalConv-Pytorch A Pytorch implementation of MalConv Desciprtion This is the implementation of MalConv proposed in Malware Detection by Eating a Whole

58 Oct 26, 2022

Adversarial Learning for Modeling Human Motion

Adversarial Learning for Modeling Human Motion This repository contains the open source code which reproduces the results for the paper: Adversarial l

6 Jun 15, 2021

AlphaNet Improved Training of Supernet with Alpha-Divergence

AlphaNet: Improved Training of Supernet with Alpha-Divergence This repository contains our PyTorch training code, evaluation code and pretrained model

87 Oct 10, 2022

Towards End-to-end Video-based Eye Tracking

Towards End-to-end Video-based Eye Tracking The code accompanying our ECCV 2020 publication and dataset, EVE. Authors: Seonwook Park, Emre Aksan, Xuco

76 Dec 12, 2022

Conservative Q Learning for Offline Reinforcement Reinforcement Learning in JAX

CQL-JAX This repository implements Conservative Q Learning for Offline Reinforcement Reinforcement Learning in JAX (FLAX). Implementation is built on

8 Nov 07, 2022

ByteTrack with ReID module following the paradigm of FairMOT, tracking strategy is borrowed from FairMOT/JDE.

ByteTrack_ReID ByteTrack is the SOTA tracker in MOT benchmarks with strong detector YOLOX and a simple association strategy only based on motion infor

46 Dec 29, 2022

This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners.

LiST (Lite Self-Training) This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners. LiST is short for Lite S

28 Dec 07, 2022

Boosted neural network for tabular data

XBNet - Xtremely Boosted Network Boosted neural network for tabular data XBNet is an open source project which is built with PyTorch which tries to co

175 Jan 04, 2023

Lipschitz-constrained Unsupervised Skill Discovery

Lipschitz-constrained Unsupervised Skill Discovery This repository is the official implementation of Seohong Park, Jongwook Choi*, Jaekyeom Kim*, Hong

17 Dec 18, 2022

Universal Adversarial Triggers for Attacking and Analyzing NLP (EMNLP 2019)

Universal Adversarial Triggers for Attacking and Analyzing NLP This is the official code for the EMNLP 2019 paper, Universal Adversarial Triggers for

248 Dec 17, 2022

This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.

optimaladj: A library for computing optimal adjustment sets in causal graphical models This package implements the algorithms introduced in Smucler, S

6 Aug 04, 2022

A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.

Reinforcement-Learning-Notebooks A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented

1k Dec 28, 2022