u/Decent_Dimension_802 — reddlx

I made github repo for reproduced of DeepANC paper

Hi everyone,

I recently put together a repository for reproducing DeepANC, which is related to Active Noise Control (ANC).

DeepANC is considered a pretty fundamental baseline when it comes to combining deep learning with ANC. However, while studying and researching, I noticed that there doesn't seem to be an official repository or widely accessible reference code available for it.

Because of that, I decided to reproduce it myself based on the original paper. The repo includes my implementation, along with the environment setup needed to train and test the model. I tried to structure it so that anyone looking for a solid starting point can easily run it.

For more detailed setup and usage instructions, please check the README.md in the repository.

Github Repo:https://github.com/johnjaejunlee95/DeepANC-reproduced

I know that diving into DL-based ANC without reference code can be a bit challenging. I hope this helps others who are studying, struggling, or experimenting with deep learning and ANC. Please take a look, and any feedback or suggestions are always welcome!! 😄😄

u/Decent_Dimension_802 — 6 days ago

▲ 6 r/optimization

A Unified PyTorch Framework for Sharpness-Aware Minimization (SAM)

Train flatter, better robustness. 🚀. I want to share my GitHub project: a Unified Sharpness-Aware Minimization (SAM) Optimizer Framework.

While working on Sharpness-Aware Minimization (SAM), I noticed that implementations of various SAM variants are scattered across different repositories, often with inconsistent training pipelines and implementation details. As a result, fair comparisons and reproducibility become challenging, frequently requiring repeated reimplementation of training pipelines just to evaluate minor differences.

Therefore, I decided to build a unified framework for Sharpness-Aware Minimization. This repository offers a concise PyTorch implementation of widely used SAM variants, making it easy to plug in new methods, run fair comparisons, and iterate quickly—without touching the core training loop.

The project is designed with both research and practical experimentation in mind. I plan to actively maintain it and continue adding new SAM variants as the literature evolves.

If you’re interested in optimization, generalization, or robust training, feel free to check it out!! Contributions and feedback are always welcome.🙌

Repo: https://github.com/johnjaejunlee95/torch-unified-sam-optimization

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u/Decent_Dimension_802 — 8 days ago

▲ 0 r/ResearchML

I made a VLA repo for fine-tuning and benchmarking

Hi everyone,

I recently put together a repository related to Vision-Language-Action (VLA) robotics models.

The repo mainly collects and organizes well-known VLA models and methods, including OpenPI, OpenVLA, and OpenVLA-OFT. I have also revised some parts based on my own experience running the models, especially around setup, fine-tuning, and simulation-based evaluation.

One thing I decided intentionally is to keep each project as an individual setup rather than merging everything into a single unified environment. The reason is that each codebase has very different dependencies, installation requirements, and runtime assumptions, so keeping them separate felt more practical and easier to maintain.

I will continue adding more notes, configurations, benchmarks, and methods as I test them myself. For now, the repo is mainly focused on VLA fine-tuning and evaluation workflows, especially with simulation benchmarks such as LIBERO and LIBERO-Plus.

For more detailed setup and usage instructions, please check the README.md files inside each subdirectory.

Github Repo: https://github.com/johnjaejunlee95/vla-finetuning-workspace

I know that experimental settings for VLA models are sometimes very challenging. I hope this helps others who are starting, struggling or experimenting with VLA models and approaches. Feedback or suggestions are welcome!! 😄😄

u/Decent_Dimension_802 — 8 days ago