MingSun-Tse

Efficient-Deep-Learning

Collection of recent methods on (deep) neural network compression and acceleration.

Collaborative-Distillation

[CVPR'20] Collaborative Distillation for Ultra-Resolution Universal Style Transfer (PyTorch)

Regularization-Pruning

[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

ASSL

[NeurIPS'21 Spotlight] Aligned Structured Sparsity Learning for Efficient Image Super-Resolution (PyTorch)

Awesome-Pruning-at-Initialization

[IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.

Awesome-Efficient-ViT

Recent Advances on Efficient Vision Transformers

Why-the-State-of-Pruning-so-Confusing

[Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning

Good-DA-in-KD

[NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective

Smile-Pruning

A generic code base for neural network pruning, especially for pruning at initialization.

smilelogging

Python logging package for easy reproducible experimenting in research

TPP

[ICLR'23] Trainability Preserving Neural Pruning (PyTorch)

SRP

[ICLR'22] PyTorch code for our paper "Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning"

Efficient-NeRF

WritingTips

"Good scientific writing is not a matter of life and death; it is much more serious than that."

UtilsHub

Context-Cluster

[ICLR 2023 Oral] Image as Set of Points

3D-Vision-Papers

awesome-NeRF

A curated list of awesome neural radiance fields papers

DLTH

EECE7311_Project_NST

Efficient_Graph_Similarity_Computation

Interpretable-Deep-Learning

MingSun-Tse

mingsun-tse.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

MMVID

[CVPR 2022] Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

nerf

Code release for NeRF (Neural Radiance Fields)

nerf-pytorch

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

pointMLP-pytorch

(ICLR 2022 poster) Official PyTorch implementation of "Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework"

R2L

Research-Utilities