A curated list of resources for using LLMs to develop more competitive grant applications.

[NeurIPS 2023] MCUFormer: Deploying Vision Transformers on Microcontrollers with Limited Memory

*That Project's project repository

On-Device Training Under 256KB Memory [NeurIPS'22]

reading conference paper using rss

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; MCUNetV3: On-Device Training Under 256KB Memory

Codes to reproduce the Inner speech Dataset publicated by Nieto et al.

Spectral-normalized Neural Gaussian Process (SNGP) implementation in PyTorch

A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

为PDF文档创建目录

Starter code for using NCH Sleep DataBank

A USB Microphone built with an INMP441 and an STM32

This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pytorch.

《Machine Learning: A Probabilistic Perspective》（Kevin P. Murphy）中文翻译和书中算法的Python实现。

PyTorch code for training MM-DistillNet for multimodal knowledge distillation. http://rl.uni-freiburg.de/research/multimodal-distill

Pytorch implementation of FNet: Mixing Tokens with Fourier Transforms by Google Research

Pytorch Implementation of SMOTE

Conversion of PyTorch Models into TFLite

μNAS is a neural architecture search (NAS) system that designs small-yet-powerful microcontroller-compatible neural networks.

FInd arena size for TensorFlow Lite models

Minimal tutorials for PyTorch

Acoustic features (MFSCs and MFCCs) for edge AI

Designs for finalist teams of the DAC System Design Contest