oppenheimer1223

Deep-Complex-Networks. [Not Official] Implementation Deep Comple Networks and Plug-in module (e.g. Neural Preprocessing Layer, ICLR 2018)

Phase-aware-Deep-Complex-UNet. [Not Official] Implementation DC-UNet, ICLR 2019

Temporal-Convolution-Resnet. [Not Official] Implementation of TC-Resnet, INTERSPEECH 2019

Digging-into-Self-Supervised-Monocular-Depth-Estimation. [Not Official] Implementation of monodepth2, ICCV 2019

Convolutions-to-Vision-Transformers. [Not Official] Implementation of CvT, Convolutions to Vision Transformers

Generative-Adversarial-Network-Tutorial. Implementation GAN for MNIST, Simpson, Pokemon

NeRF-Representing-Scenes-as-Neural-Radiance-Fields-for-View-Synthesis. [Not Official] Simple NeRF training pipeline, ECCV 2020

Awesome-Developer-Resource. 이 레포지토리는 저의 관심사 그리고 유용한 개발 정보를 수록해놓았습니다.

Neural-Network-Pruning-Tutorial. Tutorial impelmentation of Neural Network Pruning for VGG

SLM-Pruning-Quantization. Pruning, Quantization recipe for Small Language Model

Microsoft-Phi-3-CookBook. This is a Phi-3 book for getting started with Phi-3. Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks.

Stand-Alone-Self-Attention. [Not Official] Implementation of Stand-Alone-Self-Attention, NeurIPS 2019

AutoAWQ. AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:

Speech-Preprocessing. Speech Data Preprocessing Tool for Deep Learning

LLM-Finetuning-Tutorial. This repository is LLM finetuning tutorial using Gemma-2B

Self-Supervised-Monocular-Sceneflow-Estimation. [Not Official] Implementation of monocular sceneflow estimation, CVPR 2020