Sunghoon Park's starred repositories

RobustSemanComm

Demo of robust semantic communication against semantic noise

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litgpt

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

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LLM-Vector-database

Construct a vector database through sentence embedding. And make your LLM respond based on this database.

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LLM-InferenceNet

LLM InferenceNet is a C++ project designed to facilitate fast and efficient inference from Large Language Models (LLMs) using a client-server architecture. It enables optimized interactions with pre-trained language models, making deployment on edge devices easier.

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dynamorio

Dynamic Instrumentation Tool Platform

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litmustestgen

Alloy models for automatic synthesis of memory model litmus test suites (from ASPLOS 2017)

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coatcheck

COATCheck

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fbzmq

Facebook ZeroMQ wrappers.

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subrosa

Leakage containment models

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IterativeClosestPoint

This is the public repo for implementing the iterative closest point algorithm.

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Zero-shot-RIS

[CVPR 2023] Official code for "Zero-shot Referring Image Segmentation with Global-Local Context Features"

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SSL-narratives-VLM-1

거꾸로 읽는 SSL 시즌3 - VLM

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SINDy

Physically-informed model discovery of systems with nonlinear, rational terms using the SINDy-PI method. Contains functionality for spectral filtering/differentiation.

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TWcmd.vim

Vim's wincmd-style tab / window moving commands (vim plugin).

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Learning-Scientific_Machine_Learning_Residual_Based_Attention_PINNs_DeepONets

Physics Informed Machine Learning Tutorials (Pytorch and Jax)

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WeightSeparation

[PerCom 2022] Weight Separation for Memory-Efficient and Accurate Deep Multitask Learning

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barlowtwins

PyTorch implementation of Barlow Twins.

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Localizable-Rotation

Official PyTorch Repository of "Tailoring Self-Supervision for Supervised Learning" (ECCV 2022 Paper)

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hls4ml

Machine learning on FPGAs using HLS

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simclr

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

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PeRFception

[NeurIPS2022] Official implementation of PeRFception: Perception using Radiance Fields.

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